# Potential alien ranges of European plants will shrink in the future, but less so for already naturalized than for not yet naturalized species

Robin Pouteau, Idoia Biurrun, Caroline Brunel, Milan Chytrý, Wayne Dawson, Franz Essl, Trevor Fristoe, Rense Haveman, Carsten Hobohm,

Florian Jansen, et al.

<figure><img src="image_1.png" /></figure>

► To cite this version:

Robin Pouteau, Idoia Biurrun, Caroline Brunel, Milan Chytrý, Wayne Dawson, et al.. Potential alien ranges of European plants will shrink in the future, but less so for already naturalized than for not yet naturalized species. Diversity and Distributions, 2021, 27 (11), pp.2063-2076. 10.1111/ddi.13378. hal-03299311

HAL Id: hal-03299311

https://hal.umontpellier.fr/hal-03299311

Submitted on 26 Jul 2021

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>
<figure><img src="image_3.png" /></figure>

RESEARCH ARTICLE

Diversity and Distributions

WILEY

# Potential alien ranges of European plants will shrink in the future, but less so for already naturalized than for not yet naturalized species

Robin Pouteau<fnref n="1" />,<fnref n="2" /> ID | Idoia Biurrun<fnref n="3" /> ID | Caroline Brunel<fnref n="1" />,<fnref n="4" /> ID | Milan Chytrý<fnref n="5" /> ID |

Wayne Dawson<fnref n="6" /> | Franz Essl<fnref n="7" /> ID | Trevor Fristoe<fnref n="8" /> | Rense Haveman<fnref n="9" /> ID |

Carsten Hobohm<fnref n="10" /> | Florian Jansen<fnref n="11" /> ID | Holger Kreft<fnref n="12" />,<fnref n="13" /> ID | Jonathan Lenoir<fnref n="14" /> ID |

Bernd Lenzner<fnref n="7" /> ID | Carsten Meyer<fnref n="15" />,<fnref n="16" />,<fnref n="17" /> ID | Jesper Erenskjold Moeslund<fnref n="18" /> ID |

Jan Pergl<fnref n="19" /> ID | Petr Pyšek<fnref n="19" />,<fnref n="20" /> ID | Jens-Christian Svenning<fnref n="21" /> ID |

Wilfried Thuiller<fnref n="22" /> ID | Patrick Weigelt<fnref n="12" />,<fnref n="23" /> ID | Thomas Wohlgemuth<fnref n="24" /> ID |

Qiang Yang<fnref n="8" /> | Mark van Kleunen<fnref n="1" />,<fnref n="8" /> ID

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

© 2021 The Authors. Diversity and Distributions published by John Wiley & Sons Ltd.

<footnote n="1">¹Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, Taizhou University, Taizhou, China</footnote>

<footnote n="2">²AMAP, Univ. Montpellier, IRD, CIRAD, CNRS, INRA, Montpellier Cedex 05, France</footnote>

<footnote n="3">³Department of Plant Biology and Ecology, Faculty of Science and Technology, University of the Basque Country UPV/EHU, Bilbao, Spain</footnote>

<footnote n="4">⁴IRD, IPME, Montpellier, France</footnote>

<footnote n="5">⁵Department of Botany and Zoology, Faculty of Science, Masaryk University, Brno, Czech Republic</footnote>

<footnote n="6">⁶Department of Biosciences, Durham University, Durham, UK</footnote>

<footnote n="7">⁷Bioinvasions, Global Change, Macroecology Group, Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria</footnote>

<footnote n="8">⁸Ecology, Department of Biology, University of Konstanz, Konstanz, Germany</footnote>

<footnote n="9">⁹Central Government Real Estate Agency of the Dutch Ministry of the Interior and Kingdom Relations, Exterior Space, Nature Department, Wageningen, The Netherlands</footnote>

<footnote n="10">¹⁰Ecology and Environmental Education Working Group, University of Flensburg (EUF), Flensburg, Germany</footnote>

<footnote n="11">¹¹Faculty of Agricultural and Environmental Sciences, University of Rostock, Rostock, Germany</footnote>

<footnote n="12">¹²Biodiversity, Macroecology & Biogeography, University of Göttingen, Göttingen, Germany</footnote>

<footnote n="13">¹³Centre of Biodiversity and Sustainable Land Use (CBL), University of Göttingen, Germany</footnote>

<footnote n="14">¹⁴UR "Ecologie et Dynamique des Systèmes Anthropisés" (EDYSAN, UMR 7058 CNRS), Université de Picardie Jules Verne, Amiens Cedex 1, France</footnote>

<footnote n="15">¹⁵German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany</footnote>

<footnote n="16">¹⁶Institute of Biology, Leipzig University, Leipzig, Germany</footnote>

<footnote n="17">¹⁷Institute for Geosciences and Geography, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany</footnote>

<footnote n="18">¹⁸Department of Bioscience, Aarhus University, Aarhus, Denmark</footnote>

<footnote n="19">¹⁹Institute of Botany, Department of Invasion Ecology, Czech Academy of Sciences, Průhonice, Czech Republic</footnote>

<footnote n="20">²⁰Department of Ecology, Faculty of Science, Charles University, Prague, Czech Republic</footnote>

<footnote n="21">²¹Center for Biodiversity Dynamics in a Changing World (BIOCHANGE) and Section for Ecoinformatics and Biodiversity, Department of Biology, Aarhus University, Aarhus C, Denmark</footnote>

<footnote n="22">²²Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, Grenoble, France</footnote>

<footnote n="23">²³Campus Institute Data Science, Göttingen, Germany</footnote>

<footnote n="24">²⁴Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland</footnote>
**Correspondence**

Robin Pouteau, AMAP, Univ. Montpellier,
IRD, CNRS, CIRAD, INRAE, Montpellier,
France.

Email: robin.pouteau@ird.fr

**Funding information**

National Natural Science Foundation of
China, Grant/Award Number: 31901176;
Taizhou University, Grant/Award Number:
2018YQ001; Basque Government, Grant/
Award Number: IT936-16; Czech Science
Foundation, Grant/Award Number:
19-28491X, 19-28807X; Austrian Science
Foundation FWF, Grant/Award Number:
I2086-B16; Freigeist Fellowship, Grant/
Award Number: A118199; German Research
Foundation, Grant/Award Number: DFG-
FZT 118, 202548816; Czech Academy of
Sciences, Grant/Award Number: 67985939;
VILLUM FONDEN, Grant/Award Number:
16549

Editor: Raimundo Real

**Abstract**

**Aims:** The rapid increase in the number of species that have naturalized beyond their native range is among the most apparent features of the Anthropocene. How alien species will respond to other processes of future global changes is an emerging concern and remains poorly misunderstood. We therefore ask whether naturalized species will respond to climate and land use change differently than those species not yet naturalized anywhere in the world.

**Location:** Global.

**Methods:** We investigated future changes in the potential alien range of vascular plant species endemic to Europe that are either naturalized (n = 272) or not yet naturalized (1,213) outside of Europe. Potential ranges were estimated based on projections of species distribution models using 20 future climate-change scenarios. We mapped current and future global centres of naturalization risk. We also analysed expected changes in latitudinal, elevational and areal extent of species' potential alien ranges.

**Results:** We showed a large potential for more worldwide naturalizations of European plants currently and in the future. The centres of naturalization risk for naturalized and non-naturalized plants largely overlapped, and their location did not change much under projected future climates. Nevertheless, naturalized plants had their potential range shifting poleward over larger distances, whereas the non-naturalized ones had their potential elevational ranges shifting further upslope under the most severe climate change scenarios. As a result, climate and land use changes are predicted to shrink the potential alien range of European plants, but less so for already naturalized than for non-naturalized species.

**Main conclusions:** While currently non-naturalized plants originate frequently from mountain ranges or boreal and Mediterranean biomes in Europe, the naturalized ones usually occur at low elevations, close to human centres of activities. As the latter are expected to increase worldwide, this could explain why the potential alien range of already naturalized plants will shrink less.

**KEYWORDS**

Alien plant species, biological invasions, climate change, distributional range shift, interacting effect of global changes, land use change, macroecology, migration, non-analogue climate, species distribution model

# 1 | INTRODUCTION

Alien species (i.e., species introduced by humans to regions outside of their native range; Essl et al., 2018; Pyšek, Richardson, Rejmánek, et al., 2004) have become a significant component of global change in the Anthropocene (Mooney & Hobbs, 2000; Seebens et al., 2017). As alien species are often considered to be “passengers” of other human-induced changes (MacDougall & Turkington, 2005), their prevalence is expected to increase by land use intensification, which is altering disturbance regimes and resource availability (D'Antonio et al., 1999; Chytrý et al., 2012; Lembrechts et al., 2016). Similarly, climate change is altering native species distributions and

community composition (Gottfried et al., 2012; Lenoir et al., 2020; Pearson et al., 2013), creating opportunities for alien species to establish or expand. Therefore, alien species' responses to land use and climate change may lead to new centres of biological invasions (Bellard et al., 2013; Dullinger et al., 2017), with the possibility for synergistic effects (Oliver & Morecroft, 2014).

Previous studies argued that global change would promote alien species by enabling population establishment and persistence, and offering new opportunities for introductions (Hellmann et al., 2008; Walther et al., 2009). Indeed, experimental studies indicate that many alien plants might take more advantage of increased CO₂ levels and temperatures than many native plants (Haeuser et al., 2017;
Liu et al., 2017). However, in a recent review of 71 publications covering 423 naturalized (i.e., alien species reproducing naturally in the recipient ecosystems) and invasive species (i.e., rapidly spreading alien species, which frequently alter the composition, structure and functioning of the recipient ecosystems), climate change was more frequently projected to contribute to a decrease in range size than an increase (Bellard et al., 2018). The underlying causes and whether this pattern remains the same when accounting for land use change are unknown.

Species that are already naturalized somewhere are also more likely to naturalize elsewhere (Daehler & Strong, 1993; Mayer et al., 2017; Pyšek et al., 2003). Nevertheless, the number of emerging naturalized species (i.e., species that had never before been recorded as naturalized) is also steadily increasing (Seebens et al., 2018). It was recently estimated that the global pool of candidate species for naturalized vascular plants is ~47,000 (Seebens et al., 2018), which is ~3.5 times larger than the current number of naturalized vascular plants (van Kleunen et al., 2019). Because species distribution models (SDMs) for alien species usually focus on those aliens that are already naturalized, and particularly those that are considered invasive, little is known about the potential future change in alien distributions when incorporating the pool of species not yet naturalized.

Different hypotheses predict that distributional patterns of naturalized and currently non-naturalized species will become either more distinct or more similar. First, the typically broad environmental tolerance of widespread naturalized and invasive species suggests that they may be less sensitive to climate change compared to currently non-naturalized species (Thuiller et al., 2005). Future changes in the potential alien ranges of naturalized species are thus expected to be of relatively smaller magnitude than those of currently non-naturalized species. Second, given their close associations with anthropogenic habitats (MacDougall & Turkington, 2005), naturalized species are expected to persist in currently occupied areas while also colonizing newly suitable areas in conjunction with land use changes. Therefore, the potential alien ranges of naturalized species are expected to expand while those of currently non-naturalized species are expected to shrink. Third, a significant proportion of species could originate from climates with no or an increasingly scarce future analogue (Williams & Jackson, 2007), leading to a decrease in their future potential alien range, which would also apply equally to naturalized and non-naturalized species. For instance, this might be the case for plant species native to the Mediterranean biome, which is predicted to become increasingly restricted (Dullinger et al., 2017). As these hypotheses predict different patterns, comparisons of expected shifts in potential alien ranges between naturalized and currently non-naturalized species of the same continent of origin may shed light on the processes that drive future changes in naturalized species distributions.

Europe is the second most important donor continent of naturalized alien plant species after Asia, but, relative to the number of native species, the European flora has by far the greatest proportion of species naturalizing on other continents (Kalusová et al., 2017;

van Kleunen et al., 2015). Of the ~14,000 vascular plant species native to Europe, 3,383 are known to be naturalized somewhere in the world, which is three times more than expected from the global average (van Kleunen et al., 2015). Furthermore, five of the ten most widely naturalized plant species globally are native to Europe (Pyšek et al., 2017). As a result, the European flora provides an excellent study system to determine whether future climate and land use changes will promote or limit the spread of naturalized species and, if so, where.

To estimate the actual and future (years 2061–2080) potential ranges of both naturalized and not yet naturalized plants outside Europe, we used ensemble species-distribution models for 1,485 European endemic plant species considering both climate and land use data. Specifically, we investigated: (1) how areas with high potential richness in alien plants native to Europe are predicted to change in the course of climate and land use changes and (2) whether changes in the potential alien distribution of species naturalized and not yet naturalized outside Europe will differ in latitude, elevation and range size.

## 2 | METHODS

### 2.1 | Modelling the potential alien ranges of plant species under current climatic and land use conditions

#### 2.1.1 | Species selection

Many plant species native to Europe are also native to other continents such as Asia and Africa, for which there are much fewer data on species occurrences in global repositories (Meyer et al., 2016). Therefore, we focused exclusively on vascular plant species endemic to Europe, as this allows us to better capture the full realized niche of the species in their native continent (Gallien et al., 2010). Here, "Europe" is used in a geographical sense and defined as bordered by the Arctic Ocean to the north, the Atlantic Ocean to the west (the Macaronesian archipelagos were excluded), the Ural Mountains and the Caspian Sea to the east and the Lesser Caucasus and the Mediterranean Sea to the south (Mediterranean islands included, Anatolia excluded; Supplementary Information Figure S1).

The most recent version of the database "Endemic vascular plants in Europe" (EvplantE; Hobohm, 2014), containing >6,200 endemic plant taxa, was used here as a baseline for species selection. Scientific names were standardized based on The Plant List (http://www.theplantlist.org/). This taxonomic standardization was done with the R package "Taxonstand" (Cayuela et al., 2017). Infraspecific taxa were excluded from the list, resulting in 4,985 species.

The naturalization status of the European endemic flora was obtained from the "Global Naturalized Alien Flora" (GloNAF) database, version 1.2, a recently compiled database of ~14,000 naturalized alien plant species (van Kleunen et al., 2019). A total of 407 European endemic species are recorded in GloNAF as naturalized somewhere in the world, and 4,578 European endemic species are not recorded
in GloNAF as naturalized, irrespective of whether they have been
introduced elsewhere or not.

2.1.2 | Compilation of occurrence records

The native range of European endemics sometimes reflects bio-
geographical barriers (e.g., mountain ranges, seas) rather than true
climatic limitations. In such cases, considering native occurrences
only would lead to climatic niche truncation and an underestima-
tion of the potential alien range of the species in our dataset (cf.
Feeley, 2015). Moreover, a problem with developing models by using
observations from the native range only is that the ecological re-
quirements of the species might have changed during the naturaliza-
tion process, thus violating the assumption of niche conservatism
(Pearman et al., 2008). To reduce these problems, we considered
native occurrences in conjunction with naturalized occurrences in
Europe. This allowed us to get a more complete picture of species
environmental niches and, therefore, to build more transferable
models with more meaningful predictions where the species could
potentially occur (Gallien et al., 2010). This pooled approach has
been shown to be particularly relevant to improve predictions of the
future extent of naturalizations (Broennimann & Guisan, 2008).

To comprehensively compile the distribution of our studied set
of endemic species in their native continent, we combined occur-
rence data in Europe from five sources. The first source was the
"Global Biodiversity Information Facility" (GBIF), one of the largest
and most widely used biodiversity databases (https://www.gbif.org/
accessed on 17 October 2018). Currently, GBIF provides access to
more than 600,000 distributional records for European endemic
plant species. Although GBIF offers a relatively good coverage of
Europe, it remains subject to taxonomic and geographical biases,
gaps and uncertainties (see Meyer et al., 2016). Records of European
endemic plants deemed erroneous were discarded (Table S1). All oc-
currences from GBIF were downloaded using the R package "rgbif"
(Chamberlain et al., 2019). The second source was the "EU-Forest"
dataset, providing information on European tree species distri-
bution, including more than half a million occurrences at a 1-km (~
50 arcsec at 50° latitude) resolution (Mauri et al., 2017). The third
source we used was the "European Vegetation Archive" (EVA), which
assembles observations from more than one million vegetation plots
across Europe (Chytrý et al., 2016). Unlike GBIF and EU-Forest data,
the EVA database includes comprehensive local plant community in-
ventories (i.e., relevés) for various life-forms. This database remains
geographically imbalanced with more data in Western, Central and
Southern Europe than in Northern and Eastern Europe, but it signifi-
cantly complements GBIF data, which are sparser in Southern and
Eastern-Central Europe. The fourth source was the digital version
of the Atlas Florae Europaea offering gridded maps. The main lim-
itations of this dataset is its coarse spatial resolution (cells of 50-
km resolution, i.e., ~ 0.70° at 50° latitude) and restricted taxonomic
coverage (~30% of the European flora; https://www.luomus.fi/en/
publishing-atlas-florae-europaea). The fifth source was the "Plant

Functional Diversity of Grasslands" network (DIVGRASS), combin-
ing data on plant diversity across ~70,000 vegetation plots in French
permanent grasslands (Violle et al., 2015). This dataset did not cover
all of Europe but was included to maximize regional information on
native distributions.

When several occurrences from these different sources were
duplicated on the same 0.42° × 0.42° grid cell (~47 km at the equa-
tor, 30 km at 50° latitude), only one record was kept to avoid pseu-
doreplication. After removing duplicate records, species with fewer
than 10 occurrences were not further considered as the resulting
SDM might be insufficiently accurate (van Proosdij et al., 2016). In
a preliminary analysis, we assessed whether SDM performance in-
creased with increasing sample sizes and found no such relation-
ships, suggesting that the minimum number of records required
to obtain reliable SDMs (asymptote) was reached (Figure S2). The
final dataset comprised 104,313 occurrences for 1,485 European
endemic species, that is, 70 occurrences per species on average
with a maximum of 957 occurrences for *Achillea ptarmica*. A total of
272 of those species (18%) were reported to be naturalized outside
Europe, and the remaining 1,213 species (82%) were considered
non-naturalized outside Europe, irrespective of whether or not they
were introduced outside Europe (Table S2; van Kleunen et al., 2019).
Almost half of species naturalized outside Europe were also natu-
ralized in Europe (127 species; 47%). One sixth (17%) of the occur-
rences for these species were located in European countries where
the species are considered as alien and the rest of available occur-
rences (83%) were found in countries where the species are consid-
ered as native. However, the exact proportion of alien occurrences
is likely to be higher as a significant number of species are native in
part of a country (e.g., *Pulmonaria officinalis* in Northern Italy) and
alien in another part (e.g., *Pulmonaria officinalis* in Southern Italy:
Figure S1), but this proportion is difficult to assess at finer scale
given the limitation that most European plant databases use coun-
tries as basic geographical unit.

2.1.3 | Environmental variables

We selected six environmental predictors related to climate, soil
physico-chemical properties and land use, commonly considered
to shape the spatial distribution of plants (Gurevitch et al., 2006).
Annual mean temperature (°C), annual sum of precipitation (mm) and
precipitation seasonality representing the period 1979–2013 were
extracted from the CHELSA climate model at a 30 arcsec resolu-
tion (Karger et al., 2017). Organic carbon content (g per kg) and soil
pH in the first 15 cm of topsoil were extracted at a 1-km resolution
from the global gridded soil information database SoilGrids (Hengl
et al., 2014). The proportion of primary land cover (land with natural
vegetation that has not been subject to human activity since 1,500)
averaged over the period 1979–2013 in each 0.42° resolution grid cell
 variable "gothr") based on the Harmonized Global Land Use dataset
was also used (Chini et al., 2014). Environmental variables were ag-
gregated at a spatial resolution of 0.42° × 0.42° to approach the cell
size of the occurrence records with the coarsest resolution (i.e., the Atlas Florae Europaea). Pairwise correlations between the six predictor variables did not exceed the threshold of $|r| = 0.70$ beyond which collinearity begins to severely distort model estimations and subsequent predictions (Figure S3; Dormann et al., 2013). However, these variables reflecting trends in average climate conditions were significantly correlated with climate extremes to which plants are recognized to be highly responsive (Zimmermann et al., 2009).

### 2.1.4 | Species distribution modelling

The potential distribution of 1,485 European endemic plant species was predicted by estimating environmental similarity to the sites of occurrence in Europe. To increase robustness of the predictions, we used six methods to generate SDMs: generalized additive models, generalized linear models (GLMs), generalized boosting trees, maximum entropy, multivariate adaptive regression splines and random forests. All of these methods require both presences and either true absences or pseudo-absences (a random subset of the available environmental conditions in the area, i.e., Europe in our case), whose selection can significantly affect predictions (Barbet-Massin et al., 2012). We performed a preliminary analysis to identify the most appropriate set of pseudo-absences for each SDM method (Appendix S1). We evaluated the predictive performance of each SDM using a repeated split sampling approach in which SDMs were calibrated over 75% of the data and evaluated over the remaining 25%. This procedure was repeated 10 times. The evaluation was performed by measuring the area under the receiver operating characteristic (ROC) curve (AUC) (Fielding & Bell, 1997) and the true skill statistic (TSS) (Allouche et al., 2006). ROC curves were constructed by using all possible thresholds to classify the scores into confusion matrices, obtaining sensitivity and specificity for each matrix, and then plotting sensitivity against the corresponding proportion of false positives. AUC values range from 0 to 1, where 1 indicates a perfect fit, and 0.5 indicates that predictions from the SDM do not differ from random, and 0 means the SDM is always incorrect. TSS is a threshold-dependent metric calculated as: sensitivity + specificity - 1. Continuous model predictions were transformed into binary ones by selecting the threshold maximizing TSS to ensure the most accurate predictions as it is based on both sensitivity and specificity (Jiménez-Valverde and Lobo 2007). TSS ranges from -1 to 1, where 1 indicates perfect agreement, 0 indicates a random prediction and negative values indicate that predictions perform worse than random.

Results of the different SDM methods were aggregated into a single consensus projection (i.e., map) to reduce uncertainties associated with each technique (Araújo & New, 2007). This approach would produce more robust predictions of plant invasion risks than those of individual SDMs (Guan et al., 2020; Stohlgren et al., 2010). To ensure the quality of the ensemble SDMs, we only kept the projections for which the accuracy estimated by AUC and TSS were higher than 0.8 and 0.6, respectively, and assembled the selected SDMs using a committee-average approach with a weight

proportional to their TSS evaluation (Marmion et al., 2009). The entire species distribution modelling process was performed within the "biomod2" R platform (Thuiller et al., 2009), and is synthesized following the standard protocol ODMAP (Overview, Data, Model, Assessment and Prediction; Zurell et al., 2020) in Appendix S2.

## 2.2 | Modelling the potential alien ranges of plant species under future climatic conditions

To model the potential spread of the European endemic flora outside of Europe in the future, we used projections for the four representative concentration pathways (RCPs) of both climate and land cover data for the period 2061-2080. Because of the substantial climatic differences predicted by different general circulation models (GCMs; Knutti & Sedlacek, 2013), which result in concomitant differences in species range projections, simulations of future climate variables were based on five different GCMs: CCSM4, CESM1-CAM5, CSIRO-mk3-6-0, IPSL-CM5A-LR and MIROC5.

For each of the 20 RCP-GCM combinations, final binary consensus maps were stacked to estimate the number of species that would find suitable environmental conditions in each grid cell (Figure S4). As in Dullinger et al. (2017), we defined centres of naturalization risk as the top 10% of cells that provide a suitable climate and land use to the highest numbers of alien species endemic to Europe for which we built SDMs. To depict potential contraction or expansion of centres of naturalization risk, we also mapped these centres by applying the top 10% cut-off value determined under current conditions to the future climatic scenarios (also see Dullinger et al., 2017). These maps were computed for naturalized plants endemic to Europe (10% cut-off value = 50 species) and for currently non-naturalized European endemics (210).

Further, we evaluated whether predicted changes in the potential alien range of naturalized and non-naturalized European endemic plant species differ in: (1) the optimum (i.e., mean value) and breadth (i.e., standard deviation) of latitude (Hirzel et al., 2002); (2) the optimum and breadth of elevation derived from the Shuttle Radar Topography Mission (SRTM) digital elevation model with an original resolution of 90 m aggregated at 0.42° × 0.42°; and (3) range size estimated in metric units using the angular to planar transformation performed by the *area* function of the "raster" R package (Hijmans et al., 2019). These variables were scaled to a mean of zero and a standard deviation of one to improve the interpretability of regression coefficients.

The latitude, elevation and size of species ranges are not completely independent (e.g., species with a larger potential alien range also tended to have a wider latitudinal breadth; *r* = 0.43). Therefore, explanatory variables were jointly compared using GLMs (with naturalization status as response variable) built for current conditions and each RCP-GCM combination. Moreover, certain taxonomic ranks were over-represented in our studied set of species (e.g., 153 species of the genus *Rubus* and 224 species of the family *Rosaceae*). Therefore, we controlled for between-species phylogenetic
<table><caption>**TABLE 1** Results of the phylogenetically controlled generalized linear models testing whether the latitude, elevation and range size of the current realized ranges in Europe (i.e., based on collected occurrence records) and the current potential ranges outside of Europe (i.e., based on the predictions of species distribution models) relate to naturalization of species endemic to Europe</caption><thead><tr><th rowspan="2"></th><th colspan="3">Latitude optimum (°)</th><th colspan="3">Latitude breadth (°)</th><th colspan="3">Elevation optimum (m)</th><th colspan="3">Elevation breadth (m)</th><th colspan="3">Range size (in no. of occurrences and million km², respectively)</th></tr><tr><th>s2</th><th>Est.</th><th>z value</th><th>p-Value</th><th>Est.</th><th>z value</th><th>p-Value</th><th>Est.</th><th>z value</th><th>p-Value</th><th>Est.</th><th>z value</th><th>p-Value</th><th>Est.</th><th>z value</th><th>p-Value</th></tr></thead><tbody><tr><td>Realized range in Europe</td><td>0.99</td><td>0.12</td><td>1.25</td><td>.213</td><td>0.54</td><td>5.89</td><td>.000</td><td>-1.13</td><td>-6.18</td><td>.000</td><td>0.84</td><td>5.45</td><td>.000</td><td>0.41</td><td>4.28</td><td>.000</td></tr><tr><td>Potential range outside Europe</td><td>1.67</td><td>0.73</td><td>5.75</td><td>.000</td><td>0.32</td><td>3.26</td><td>.001</td><td>-0.38</td><td>-3.56</td><td>.000</td><td>-0.30</td><td>-1.28</td><td>.202</td><td>0.39</td><td>3.68</td><td>.000</td></tr></tbody></table>

Note: Explanatory variables were centred and standardized. s2 denotes the strength of the phylogenetic signal, estimate (Est.) is the amount by which the log odds of naturalization status (0 = not yet naturalized, 1 = already naturalized) would increase if range characteristics were one standard deviation higher and z value is the logistic regression correlation coefficient. Values in bold indicate significant p-values (<.050).

distances in comparisons between naturalized and non-naturalized species (for details on the phylogeny used, see Supplementary Information Appendix S3). Phylogenetically controlled GLMs were performed using the binaryPGLMM() function of the R package "ape" (Paradis et al., 2020). In this function, s2 is the scaling component of the variance in the model, where s2 = 0 suggests no phylogenetic signal and a high s2 value implies strong phylogenetic signal (Nakagawa & Schielzeth, 2013). Our GLMs had an s2 parameter in the range 0.99-1.67, indicating a very strong phylogenetic signal (Tables 1 and 2; Table S3).

## 3 | RESULTS

Plant species endemic to Europe and naturalized outside Europe had significantly more occurrence records within Europe than European endemic plant species not yet naturalized elsewhere (Table 1). For example, nine of the ten most common species in European plant databases were naturalized outside of Europe. Occurrence records in Europe indicated that naturalized species occupy cooler, drier, more climatically stable and more disturbed sites with soils richer in organic C and more acidic than sites occupied by non-naturalized species (Supplementary Information Figure S5). The former were also more tolerant to variations in the six environmental variables selected for species distribution modelling than the latter (Figure S5). In their native European range, the collected occurrence records showed that naturalized species occurred at lower elevation and had a higher latitudinal and elevational breadth than non-naturalized species (Table 1). Still, the two groups had their current average climatic optimum at similar latitude (Table 1 and Figure S6). As observed in the native range, naturalized species were predicted to find suitable conditions outside of Europe at a lower elevation and in a wider range of latitudes than non-naturalized species (Table 1). However, in contrast to their occurrences in Europe, naturalized species had their climatic optimum more poleward than non-naturalized species outside their native European range, while naturalized and non-naturalized species had a similar potential elevational range (Table 1).

The six major centres of naturalization risk of plant species endemic to Europe are the southeast of North America, Central America, the Andes, the South American pampas, the Central African mountains, temperate Australia and New Zealand and eastern China, independently of whether or not these endemic species are currently naturalized elsewhere (Figure 1). Indeed, the global overlap in the areas identified as current or future centres of naturalization risks is very large between species endemic to Europe already naturalized outside Europe and those not yet naturalized elsewhere. This pattern remained largely the same under different scenarios of future climate and land use changes (Figure 1).

The size of the future potential alien range of European endemic plants already naturalized outside Europe was predicted to decrease both in absolute value (Figure S7) and relative to the present potential range outside Europe (Figure 2) in all but three RCP-GCM combinations (2.6-CESM1-CAM5, 8.5-CESM1-CAM5 and 8.5-MIROC5).
<table><caption>TABLE 2 Results of the phylogenetically controlled generalized linear models testing whether predicted changes in latitude, elevation and range size (in % to the present range) between the current (1979–2013) and future (2061–2080) potential alien ranges relate to naturalization of species endemic to Europe</caption><thead><tr><th rowspan="2">RCP</th><th rowspan="2">GCM</th><th colspan="3">Change in latitude optimum (°)</th><th colspan="3">Change in latitude breadth (°)</th><th colspan="3">Change in elevation optimum (m)</th><th colspan="3">Change in elevation breadth (m)</th><th colspan="3">Change in range size (% to present)</th></tr><tr><th>s2</th><th>Est.</th><th>z value</th><th>p-Value</th><th>Est.</th><th>z value</th><th>p-Value</th><th>Est.</th><th>z value</th><th>p-Value</th><th>Est.</th><th>z value</th><th>p-Value</th><th>Est.</th><th>z value</th><th>p-Value</th></tr></thead><tbody><tr><td>2.6</td><td>CCSM4</td><td>1.36</td><td>-0.01</td><td>-0.08</td><td>.935</td><td>-0.10</td><td>-0.81</td><td>.420</td><td>0.33</td><td>1.55</td><td>.122</td><td>-0.12</td><td>-0.57</td><td>.571</td><td>0.20</td><td>1.79</td><td>.074</td></tr><tr><td>-</td><td>CESM1-CAM5</td><td>1.33</td><td>0.14</td><td>1.20</td><td>.229</td><td>-0.17</td><td>-1.37</td><td>.170</td><td>0.21</td><td>1.34</td><td>.181</td><td>-0.02</td><td>-0.11</td><td>.910</td><td>0.27</td><td>2.51</td><td>.012</td></tr><tr><td>-</td><td>CSIRO-mk3-6-0</td><td>1.33</td><td>0.06</td><td>0.56</td><td>.579</td><td>-0.17</td><td>-1.52</td><td>.128</td><td>0.46</td><td>3.05</td><td>.002</td><td>-0.42</td><td>-2.63</td><td>.009</td><td>0.19</td><td>1.80</td><td>.072</td></tr><tr><td>-</td><td>IPSL-CM5A-LR</td><td>1.41</td><td>0.20</td><td>1.83</td><td>.067</td><td>-0.19</td><td>-3.00</td><td>.086</td><td>0.39</td><td>2.09</td><td>.037</td><td>-0.38</td><td>-2.22</td><td>.027</td><td>0.27</td><td>2.62</td><td>.009</td></tr><tr><td>-</td><td>MIROC5</td><td>1.33</td><td>0.18</td><td>1.59</td><td>.112</td><td>-0.20</td><td>-1.78</td><td>.075</td><td>0.21</td><td>1.30</td><td>.196</td><td>-0.18</td><td>-1.05</td><td>.293</td><td>0.29</td><td>2.75</td><td>.006</td></tr><tr><td>4.5</td><td>CCSM4</td><td>1.36</td><td>0.48</td><td>4.19</td><td>.000</td><td>-0.32</td><td>-2.78</td><td>.006</td><td>-0.03</td><td>-0.16</td><td>.873</td><td>0.02</td><td>0.12</td><td>.906</td><td>0.36</td><td>3.63</td><td>.000</td></tr><tr><td>-</td><td>CESM1-CAM5</td><td>1.27</td><td>0.59</td><td>5.47</td><td>.000</td><td>-0.12</td><td>-1.15</td><td>.251</td><td>-0.00</td><td>-0.02</td><td>.987</td><td>0.04</td><td>0.28</td><td>.779</td><td>0.19</td><td>1.97</td><td>.048</td></tr><tr><td>-</td><td>CSIRO-mk3-6-0</td><td>1.33</td><td>0.14</td><td>1.68</td><td>.094</td><td>-0.12</td><td>-1.30</td><td>.193</td><td>0.25</td><td>2.02</td><td>.044</td><td>-0.10</td><td>-0.97</td><td>.333</td><td>0.24</td><td>2.70</td><td>.007</td></tr><tr><td>-</td><td>IPSL-CM5A-LR</td><td>1.28</td><td>0.41</td><td>4.59</td><td>.000</td><td>-0.20</td><td>-2.02</td><td>.043</td><td>0.17</td><td>1.38</td><td>.168</td><td>-0.23</td><td>-2.11</td><td>.035</td><td>0.28</td><td>3.26</td><td>.001</td></tr><tr><td>-</td><td>MIROC5</td><td>1.28</td><td>0.38</td><td>3.90</td><td>.000</td><td>-0.16</td><td>-1.62</td><td>.105</td><td>-0.01</td><td>-0.10</td><td>.924</td><td>0.08</td><td>0.58</td><td>.562</td><td>0.32</td><td>3.43</td><td>.001</td></tr><tr><td>6.0</td><td>CCSM4</td><td>1.33</td><td>0.34</td><td>3.19</td><td>.001</td><td>-0.30</td><td>-2.66</td><td>.008</td><td>-0.06</td><td>-0.33</td><td>.740</td><td>0.04</td><td>0.19</td><td>.847</td><td>0.38</td><td>3.40</td><td>.001</td></tr><tr><td>-</td><td>CESM1-CAM5</td><td>1.35</td><td>0.44</td><td>4.48</td><td>.000</td><td>-0.18</td><td>-1.54</td><td>.123</td><td>-0.16</td><td>-1.08</td><td>.282</td><td>0.12</td><td>0.76</td><td>.448</td><td>0.21</td><td>1.96</td><td>.050</td></tr><tr><td>-</td><td>CSIRO-mk3-6-0</td><td>1.37</td><td>0.26</td><td>2.63</td><td>.009</td><td>-0.27</td><td>-2.55</td><td>.011</td><td>0.02</td><td>0.14</td><td>.890</td><td>0.01</td><td>0.06</td><td>.954</td><td>0.33</td><td>3.11</td><td>.002</td></tr><tr><td>-</td><td>IPSL-CM5A-LR</td><td>1.30</td><td>0.37</td><td>4.19</td><td>.000</td><td>-0.34</td><td>-3.05</td><td>.002</td><td>0.03</td><td>0.21</td><td>.835</td><td>-0.20</td><td>-1.43</td><td>.154</td><td>0.37</td><td>3.59</td><td>.000</td></tr><tr><td>-</td><td>MIROC5</td><td>1.28</td><td>0.42</td><td>4.35</td><td>.000</td><td>-0.24</td><td>-2.25</td><td>.025</td><td>-0.04</td><td>-0.29</td><td>.776</td><td>0.03</td><td>0.18</td><td>.860</td><td>0.32</td><td>3.19</td><td>.001</td></tr><tr><td>8.5</td><td>CCSM4</td><td>1.35</td><td>0.39</td><td>5.64</td><td>.000</td><td>0.01</td><td>0.13</td><td>.899</td><td>-0.17</td><td>-1.23</td><td>.220</td><td>-0.02</td><td>-0.19</td><td>.852</td><td>0.10</td><td>1.22</td><td>.223</td></tr><tr><td>-</td><td>CESM1-CAM5</td><td>1.30</td><td>0.35</td><td>5.47</td><td>.000</td><td>0.03</td><td>0.41</td><td>.685</td><td>-0.24</td><td>-2.12</td><td>.034</td><td>0.13</td><td>1.12</td><td>.261</td><td>0.09</td><td>1.20</td><td>.232</td></tr><tr><td>-</td><td>CSIRO-mk3-6-0</td><td>1.44</td><td>0.24</td><td>3.94</td><td>.000</td><td>-0.01</td><td>-0.11</td><td>.913</td><td>-0.02</td><td>-0.16</td><td>.873</td><td>-0.00</td><td>-0.02</td><td>.982</td><td>0.21</td><td>2.68</td><td>.007</td></tr><tr><td>-</td><td>IPSL-CM5A-LR</td><td>1.31</td><td>0.35</td><td>6.40</td><td>.000</td><td>0.06</td><td>0.81</td><td>.419</td><td>-0.10</td><td>-0.91</td><td>.365</td><td>-0.12</td><td>-1.28</td><td>.200</td><td>0.08</td><td>1.19</td><td>.235</td></tr><tr><td>-</td><td>MIROC5</td><td>1.31</td><td>0.39</td><td>6.34</td><td>.000</td><td>0.06</td><td>0.75</td><td>.456</td><td>-0.06</td><td>-0.57</td><td>.572</td><td>-0.07</td><td>-0.57</td><td>.568</td><td>0.10</td><td>1.46</td><td>.145</td></tr></tbody></table>

Note: Explanatory variables were centred and standardized. s2 denotes the strength of the phylogenetic signal, estimate (Est.) is the amount by which the log odds of naturalization status (0 = not yet naturalized, 1 = already naturalized) would increase if range characteristics were standard deviation higher and z value is the logistic regression correlation coefficient. Values in bold indicate significant p-values (<.050).

Abbreviations: GCM, general circulation models; RCP, representative concentration pathways
<figure><img src="image_4.png" /></figure>

**FIGURE 1** Potential centres of naturalization risk of plant species endemic to Europe that are naturalized somewhere in the world ("Nat."; left column) and currently non-naturalized ("Non-nat."; right column). Present hotspots are displayed in blue, future (2061–2080) hotspots in red and the overlap between both in yellow. These maps were obtained by stacking 272 naturalized species distribution models (SDMs) and 1,213 non-naturalized SDMs, and then selecting the 10% of cells that provide a suitable climate and land-use to the highest numbers of species in each stack. This top 10% cut-off value was determined under current conditions (50 naturalized species and 210 non-naturalized species) and applied to the most extreme climate representative concentration pathways (RCPs 2.6 and 8.5). Potential species richness of each RCP was obtained by calculating the median value of five global circulation models (CCSM4, CESM1-CAM5, CSIRO-mk3-6-0, IPSL-CM5A-LR and MIROC5)

The same applies to European endemic plants not yet naturalized outside Europe for all scenarios. Nevertheless, the future potential range size for naturalized species decreased significantly less (mean change for all RCP-GCM combinations = -0.3 million km²) than for non-naturalized species (-0.5 million km²; Tables 2 and S3).

Naturalized and non-naturalized species were both projected to have wider potential latitudinal ranges in the future than at present, but less so for naturalized species than for non-naturalized species (Table 2). However, the potential alien ranges of naturalized species are expected to move further poleward (mean shift for all RCP-GCM combinations = +1.5° latitude over 70-80 years) than those of currently non-naturalized species (+1.0° latitude), and this was more pronounced for the most severe climate change scenarios (Tables 2 and Table S3). Potential alien ranges are expected to move to higher elevations too. However, while the potential alien ranges of naturalized species will move further upslope than those of currently non-naturalized species under the most moderate climate change scenarios (RCP 2.6; mean shift = +61 and +54 m, respectively), this was not true, and even reversed, for the most severe climate change scenarios (RCP 8.5; +78.5 and +107 m, respectively; Tables 2 and S3). Generally, the studied species will be able to potentially occupy a broader range of elevations than at present, and this tendency was significantly greater for the non-naturalized species in many RCP-GCM combinations (Tables 2 and Table S3).

4 | DISCUSSION

Our results indicate that European endemic plants that have naturalized elsewhere in the world are more widespread and occur at

lower elevations in Europe than the ones that have not naturalized elsewhere. In line with the higher elevation distributions of the non-naturalized species within Europe, their projected ranges outside Europe also included higher elevations than for species that have become naturalized. Non-naturalized species are more likely to be habitat specialists, being more often associated with seasonal, less productive or natural conditions in Europe than naturalized species. However, the two groups do not differ in elevational breadth of their potential alien range outside Europe. The non-naturalized species are also projected to occur at more equatorial latitudes and to have a narrower latitudinal breadth than naturalized species outside of Europe. Overall, our results indicate that the naturalized and non-naturalized endemic European plants differ in distributional characteristics in their native range as well as in the projected potential alien distributions outside of Europe.

We identified six global centres where many plant species endemic to Europe would be able to naturalize (Figure 1). These potential centres were similar for naturalized and non-naturalized plants, and their locations will not change much under projected future climates. Nevertheless, our modelling approach indicates that naturalized species will have their potential alien range shifting poleward over larger distances than currently non-naturalized species, whereas the non-naturalized ones will have their potential elevational ranges shifting further upslope than the ones from the naturalized species, at least under the most extreme RCP scenario (Table 2; Table S3). Overall, climate and land use changes are expected to shrink the potential alien ranges of European endemic plants outside Europe, but less so for already naturalized than for currently non-naturalized species (Table 2; Table S3). Nevertheless,
**FIGURE 2** Predicted change in potential range size outside Europe (in % to the present range) of European endemic plants naturalized outside Europe ("Nat."); red) and European endemic plants not naturalized outside Europe ("Non-nat."); blue) for 2061-2080 according to different combinations of representative concentration pathways (RCPs, columns) and global circulation models (GCMs, rows). Comparisons have been performed using phylogenetically controlled generalized linear models. ns indicates *p*-Value >.05, *.05 > *p*-Value ≥ .01, **.01 > *p*-Value ≥ .001 and ***-*p*-Value < .001. Boxplots depict the median (heavy horizontal line), the quartiles (lower and upper edges of the box) and the minimum and maximum values excluding outliers (vertical whiskers)

<figure><img src="image_5.png" /></figure>

our study shows that many European species will have the potential to establish in regions where they currently do not occur.

Like many other studies (Pyšek et al., 2009; Rejmánek, 1996), we found that species that are more widespread in their native range are more likely to naturalize elsewhere (Table 1). One possible explanation is that species that are more widespread in their native ranges have a larger environmental niche breadth (Figure S5), and also that they are less dependent on obligate mutualisms (Pyšek et al., 2019). Hence, ubiquitous and thus more frequently recorded species are commonly better invaders (Thuiller et al., 2012). This is also supported by other studies on naturalization success of European species in North America, where one of the strongest predictors was species niche breadth in the native range (Kalusová et al., 2017; Pyšek et al., 2015). Other potential explanations include that naturalized species are better dispersers than non-naturalized species, and that species that are common in their native range are more likely to have been picked up from the native range and widely introduced (van Kleunen et al., 2007; Novoa et al., 2016; Pyšek et al., 2004). The fact that many European endemic species have failed to naturalize, although many of them would have suitable environments outside

Europe, could thus reflect that they were introduced less widely or not at all. A major pathway for the introduction of alien plants is their cultivation for ornamental and other economic value such as for animal fodder and medicines (van Kleunen et al., 2020). Indeed, we found that the percentage of ornamental (30.2%) and other economic plants (19.1%) among naturalized European endemics is much higher than among European endemics that have not yet become naturalized (4.3% and 2.4%, Pouteau, Thuiller, et al., 2021). Ongoing globalization will continue to result in species introductions, so it is likely that more of the currently non-naturalized species will be introduced elsewhere, and could naturalize.

Surprisingly, although naturalized and non-naturalized species occur on average at similar latitudes in their native European range, the projected potential latitudinal optima differed significantly between both groups (Table 1). Possibly, this reflects that although many naturalized species occur at temperate mid-latitudes in Europe, many non-naturalized species occur at high (subpolar climate) and low (Mediterranean climate) latitudes (Figure S6). Therefore, the averaged latitudinal optima within Europe of both groups largely overlap.
The fact that naturalized species occur more frequently in less
natural habitats than currently non-naturalized species (Figure S5g),
and that the former have their current elevational optima in Europe
at lower elevations (Table 1), where human populations are denser,
suggests that they have been picked up and introduced (intention-
ally or unintentionally) outside of Europe more frequently (Dostál
et al., 2012; Kalusová et al., 2017; Prinzing et al., 2002). Indeed, van
Kleunen et al. (2007) found that southern African Iridaceae were
more likely to be used in international horticulture when they came
from lower elevations. A similar idea would be that species that
succeeded to naturalize are likely to benefit from anthropogenic
activities (Alexander et al., 2016; MacDougall & Turkington, 2005),
which are more intense and widespread at low elevations, while
other species might have found refugia in the smaller high elevation
habitats. Another possible explanation would be that both species
groups have been picked up with the same frequency but, as non-
naturalized species are more likely to be habitat specialists (i.e., with
a narrower niche breadth; Figure S5), they might be less likely to be
introduced to habitats with suitable conditions.

Considering that naturalized species are associated with anthro-
pogenic habitats and that these habitats are expected to expand
poleward (Figure S8), it is not surprising that the potential alien
range of naturalized species is expected to shift poleward in latitude
over larger distances than that of currently non-naturalized species
(Table 2 and Table S3). However, given that non-naturalized species
currently occur at higher elevations in Europe (Table 1), their future
potential alien range would have been expected to be distributed at
higher elevations than that of naturalized species, which was only
true under the most pessimistic RCP (Table 2 and Table S3). Indeed,
unlike the relationship between elevation and temperature, the
relationship between elevation and precipitation can be idiosyn-
cratic (Basist et al., 1994), so that precipitation changes should not
be expected to cause coordinated directional shifts in species ele-
vations (Lenoir et al., 2010; Stephenson and Das, 2011; Crimmins
et al., 2011). Moreover, there are important between-GCM discrep-
ancies in future precipitation patterns (e.g., on islands as pointed out
by Harter et al., 2015), resulting in different responses of species
distributions to climate change. As a result, predicted future po-
tential alien ranges would be spatially patchy and highly uncertain
(Breshears et al., 2011).

Overall, our findings show that the size of the future suitable
alien range of European plant species that have become naturalized
is more often expected to decrease than increase. This confirms the
tendency for a decrease in suitable range sizes for invasive organ-
isms with future climate and land use change found in a systematic
review by Bellard et al. (2018). By contrast, Haeuser et al. (2018)
found that in Europe, the potential ranges of alien species will more
often increase than decrease, although the difference was mini-
mal. They also found that this applied to both naturalized and cur-
rently non-naturalized alien cultivated species, whereas we found
that the future potential alien range will be smaller to a greater ex-
tent for currently non-naturalized European endemic plant species
than for naturalized ones. Because both naturalized and currently

non-naturalized species were predicted to shift poleward but natu-
ralized species are predicted to shift further, this difference in range
contraction cannot be directly attributed to the decrease in the
available area as latitude increases (as a consequence of the spheri-
cal shape of the Earth). Furthermore, as we found inconsistent shifts
along the elevation gradient according to RCP-GCM combinations
between naturalized and currently non-naturalized species, this pat-
tern cannot be attributed to an elevational shift either (because the
rough conical shape of mountains provides smaller potential areas
for species as elevation increases, but see Elsen and Tingley 2015).
A possible explanation could be that naturalized species, which are
frequently associated with anthropogenic habitats, such as arable
land or ruderal places (Kalusová et al., 2017; Figure S5g), are tak-
ing advantage of land conversion. However, this would imply that
differences between naturalized and currently non-naturalized spe-
cies (i.e., the estimates) become larger when scenarios become in-
creasingly pessimistic, but our data did not support this hypothesis
(Table 2 and Table S3).

The apparent decrease in potential alien range size of natural-
ized and currently non-naturalized species may at least in part be
driven by suitable climate and land use conditions in the future not
aligned with suitable soil conditions. The heterogeneous changes in
precipitation in conjunction with the relatively linear change in tem-
perature and the expansion of anthropogenic encroachments over a
mosaic of soils may lead to novel environmental combinations in the
future (Williams & Jackson, 2007). Yet, SDMs cannot forecast how
species will respond to non-analogue situations (Bellard et al., 2018;
Fitzpatrick & Hargrove, 2009; Heikkinen et al., 2006). This could
explain why both naturalized and currently non-naturalized species
are projected to experience a decrease in the size of their potential
range according to our current knowledge.

A remaining question is why the potential alien range of currently
non-naturalized species is projected to shrink more significantly
than that of naturalized species. We showed that a key ecological
difference between the two groups is that naturalized species favour
anthropogenic habitats located at low elevations, while currently
non-naturalized species occupy higher elevation and non-temperate
(i.e., boreal-arctic or Mediterranean) latitudes in Europe (Figure S6).
Yet, the surface area occupied by anthropogenic habitats will likely
increase in the future (Figure S8), while novel climate combinations
are recognized to typically coincide with areas of boreal-arctic and
Mediterranean climate and high elevations (Ackerly et al., 2010;
Dullinger et al., 2017; Forester et al., 2013; Stralberg et al., 2009).
Thus, although there are substantial uncertainties about whether
or not the potential alien range of naturalized and currently non-
naturalized species will decline in response to climate and land use
changes, our results show that naturalized species will be less ex-
posed to potentially unsuitable novel climatic conditions than cur-
rently non-naturalized species.

In conclusion, our results suggest that vascular plant species
endemic to Europe already naturalized elsewhere in the world are
likely to benefit from future climate and land use change relative to
vascular plant species endemic to Europe that have not successfully
naturalized yet, even if these changes overall will put negative pressure on most species. We showed that species already naturalized outside Europe occur more in the lowlands of Europe, closer to human populations, than species currently not naturalized elsewhere. As they currently have different distributions in their native continent, it makes sense that they will also have different future ranges in their naturalized range outside Europe. A key difference could be their exposure to non-analogue future climates, with currently non-naturalized species probably facing more frequently uncertain novel climates than naturalized species. This could explain why the potential alien ranges of currently non-naturalized species are expected to be more impacted by climate and land use change than those of naturalized alien species. Importantly, as most European endemic species have not yet filled their current potential alien ranges, we can still expect an increase in naturalization of European plants overall, and especially in the six global centres of naturalization risk, even when the future potential ranges will decrease.

## ACKNOWLEDGEMENTS

We thank Marten Winter (iDiv, Germany) and all who contributed to the GloNAF and EVA databases without whom this work would not have been possible. Robin Pouteau was supported by the National Natural Science Foundation of China (grant number 31901176) and Taizhou University (2018YQ001). Idoia Biurrun was supported by the Basque Government (IT936-16). Milan Chytrý was supported by the Czech Science Foundation (19-28491X). Franz Essl and Bernd Lenzner appreciate funding by the Austrian Science Foundation FWF (I2086-B16). Carsten Meyer acknowledges funding by the Volkswagen Foundation through a Freigeist Fellowship (A118199), and additional support by iDiv, funded by the German Research Foundation (DFG-FZT 118, 202548816). Petr Pyšek and Jan Pergl were supported by EXPRO grant (19-28807X) of the Czech Science Foundation and long-term research development project RVO (67985939) of Czech Academy of Sciences. Jens-Christian Svenning considers this work a contribution to his VILLUM Investigator project "Biodiversity Dynamics in a Changing World" funded by VILLUM FONDEN (16549). We appreciate the helpful comments by three anonymous reviewers and the Handling Editor, Raimundo Real.

## CONFLICT OF INTEREST

The authors declare no conflict of interest.

## PEER REVIEW

The peer review history for this article is available at https://publio ns.com/publon/10.1111/ddi.13378.

## DATA AVAILABILITY STATEMENT

The data supporting the findings of this study (naturalized plant inventories, occurrence records and environmental variables) came from openly accessible repositories cited in the manuscript (for details on the EVA database, see http://euroveg.org/eva-database-obtaining-data). All present and future habitat suitability raster files are available from the Dryad Digital Repository: https://datad

ryad.org/stash/dataset/doi:10.5061/dryad.qv9s4mwf3 (Pouteau, Biurrun, et al., 2021).

## ORCID

Robin Pouteau https://orcid.org/0000-0003-3090-6551

Idoia Biurrun https://orcid.org/0000-0002-1454-0433

Caroline Brunel https://orcid.org/0000-0002-0705-5165

Milan Chytrý https://orcid.org/0000-0002-8122-3075

Franz Essl https://orcid.org/0000-0001-8253-2112

Rense Haveman https://orcid.org/0000-0001-9127-4549

Florian Jansen https://orcid.org/0000-0002-0331-5185

Holger Kreft https://orcid.org/0000-0003-4471-8236

Jonathan Lenoir https://orcid.org/0000-0003-0638-9582

Bernd Lenzner https://orcid.org/0000-0002-2616-3479

Carsten Meyer https://orcid.org/0000-0003-3927-5856

Jesper Erenskjold Moeslund https://orcid.

org/0000-0001-8591-7149

Jan Pergl https://orcid.org/0000-0002-0045-1974

Petr Pyšek https://orcid.org/0000-0001-8500-442X

Jens-Christian Svenning https://orcid.

org/0000-0002-3415-0862

Wilfried Thuiller https://orcid.org/0000-0002-5388-5274

Patrick Weigelt https://orcid.org/0000-0002-2485-3708

Thomas Wohlgemuth https://orcid.org/0000-0002-4623-0894

Mark van Kleunen https://orcid.org/0000-0002-2861-3701

## REFERENCES

Ackerly, D. D., Loarie, S. R., Cornwell, W. K., Weiss, S. B., Hamilton, H., Branciforte, R., & Kraft, N. J. B. (2010). The geography of climate change: Implications for conservation biogeography. *Diversity and Distributions*, 16, 476–487. https://doi.org/10.1111/j.1472-4642.2010.00654.x

Alexander, J. M., Lembrechts, J. J., Cavieres, L. A., Daehler, C., Haider, S., Kueffer, C., Liu, G., McDougall, K., Milbau, A., Pauchard, A., Rew, L. J., & Seipel, T. (2016). Plant invasions into mountains and alpine ecosystems: Current status and future challenges. *Alpine Botany*, 126, 89–103. https://doi.org/10.1007/s00035-016-0172-8

Allouche, O., Tsoar, A., & Kadmon, R. (2006). Assessing the accuracy of species distribution models: Prevalence, kappa and the true skill statistic (TSS). *Journal of Applied Ecology*, 46, 1223–1232. https://doi.org/10.1111/j.1365-2664.2006.01214.x

Araújo, M. B., & New, M. (2007). Ensemble forecasting of species distributions. *Trends in Ecology and Evolution*, 22, 42–47. https://doi.org/10.1016/j.tree.2006.09.010

Barbet-Massin, M., Jiguet, F., Albert, C. H., & Thuiller, W. (2012). Selecting pseudo-absences for species distribution models: How, where and how many? *Methods in Ecology and Evolution*, 3, 327–338. https://doi.org/10.1111/j.2041-210X.2011.00172.x

Basist, A., Bell, G. D., & Meentemeyer, V. (1994). Statistical relationships between topography and precipitation patterns. *Journal of Climatology*, 7, 1305–1315. https://doi.org/10.1175/1520-0442(1994)007<1305:SRBTAP>2.0.CO;2

Bellard, C., Jeschke, J. M., Leroy, B., & Mace, G. M. (2018). Insights from modeling studies on how climate change affects invasive alien species geography. *Ecology and Evolution*, 8, 5688–5700. https://doi.org/10.1002/ece3.4098

Bellard, C., Thuiller, W., Leroy, B., Genovesi, P., Bakkenes, M., & Courchamp, F. (2013). Will climate change promote future invasions? *Global Change Biology*, 19, 3740–3748. https://doi.org/10.1111/gcb.12344
Breshears, D. D., López-Hoffman, L., & Graumlich, L. J. (2011). When eco-system services crash: Preparing for big, fast, patchy climate change. *Ambio*, 40, 256–263. https://doi.org/10.1007/s13280-010-0106-4

Broennimann, O., & Guisan, A. (2008). Predicting current and future bi-ological invasions: Both native and invaded ranges matter. *Biology Letters*, 4, 585–589. https://doi.org/10.1098/rsbl.2008.0254

Cayuela, L., Stein, A., & Oksanen, J. (2017). *Taxonstand: taxonomic standardization of plant species names* v.2.1. R Foundation for Statistical Computing. Retrieved from https://cran.r-project.org/web/packages/Taxonstand/index.html

Chamberlain, S., Barve, V., Desmet, P., Geffert, L., Mcglinn, D., Oldoni, D., & Ram, K. (2019). *rgbf: interface to the Global 'Biodiversity' Information Facility* API v.1.3.0. R Foundation for Statistical Computing. Retrieved from https://cran.r-project.org/web/packages/rgbf/index.html

Chini, L. P., Hurtt, G. C., & Frolkling, S. (2014). *Harmonized Global Land Use for Years 1500–2100, V1. Data set*. Oak Ridge National Laboratory Distributed Active Archive Center, USA. Retrieved from http://daac.ornl.gov

Chytrý, M., Hennekens, S. M., Jiménez-Alfaro, B., Knollová, I., Dengler, J., Jansen, F., Landucci, F., Schaminée, J. H. J., Aćić, S., Agrillo, E., Ambarli, D., Angelini, P., Apostolova, I., Attorre, F., Berg, C., Bergmeier, E., Biurrun, I., Botta-Dukát, Z., Brisse, H., ... Yamalov, S. (2016). European Vegetation Archive (EVA): An integrated database of European vegetation plots. *Applied Vegetation Science*, 19, 173–180. https://doi.org/10.1111/avsc.12191

Chytrý, M., Wild, J., Pyšek, P., Jarošík, V., Dendoncker, N., Reginster, I., Pino, J., Maskell, L. C., Vilà, M., Pergl, J., Kühn, I., Spangenberg, J. H., & Settele, J. (2012). Projecting trends in plant invasions in Europe under different scenarios of future land-use change. *Global Ecology and Biogeography*, 21, 75–87. https://doi.org/10.1111/j.1466-8238.2010.00573.x

Crimmins, S. M., Dobrowski, S. Z., Greenberg, J. A., Abatzoglou, J. T., & Mynsberge, A. R. (2011). Changes in climatic water balance drive downhill shifts in plant species' optimum elevations. *Science*, 331, 324–327. https://doi.org/10.1126/science.1199040

Daehler, C. C., & Strong, D. R. (1993). Predictions and biological invasions. *Trends in Ecology and Evolution*, 8, 380.

D'Antonio, C. M., Dudley, T. L., & Mack, M. C. (1999). Disturbance and biological invasions: Direct effects and feedbacks. In L. R. Walker (Ed.), *Ecosystems of disturbed ground* (pp. 413–452). Elsevier.

Dormann, C. F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G., Marquéz, J. R. G., Gruber, B., Lafourcade, B., Leitão, P. J., Münkemüller, T., McClean, C., Osborne, P. E., Reineking, B., Schröder, B., Skidmore, A. K., Zurell, D., & Lautenbach, S. (2013). Collinearity: A review of methods to deal with it and a simulation study evaluating their performance. *Ecography*, 36, 27–46. https://doi.org/10.1111/j.1600-0587.2012.07348.x

Dostál, P., Dawson, W., van Kleunen, M., Keser, L. H., & Fischer, M. (2012). Central European plant species from more productive habitats are more invasive at a global scale. *Global Ecology and Biogeography*, 22, 64–72. https://doi.org/10.1111/j.1466-8238.2011.00754.x

Dullinger, I., Wessely, J., Bossdorf, O., Dawson, W., Essl, F., Gattringer, A., Klonner, G., Kreft, H., Kuttner, M., Moser, D., Pergl, J., Pyšek, P., Thuiller, W., van Kleunen, M., Weigelt, P., Winter, M., & Dullinger, S. (2017). Climate change will increase the naturalization risk from garden plants in Europe. *Global Ecology and Biogeography*, 26, 43–53. https://doi.org/10.1111/geb.12512

Elsen, P. R., & Tingley, M. W. (2015). Global mountain topography and the fate of montane species under climate change. *Nature Climate Change*, 5, 772–776. https://doi.org/10.1038/nclimate2656

Essl, F., Bacher, S., Genovesi, P., Hulme, P. E., Jeschke, J. M., Katsanevakis, S., Kowarik, I., Kühn, I., Pyšek, P., Rabitsch, W., Schindler, S., van Kleunen, M., Vilà, M., Wilson, J. R. U., & Richardson, D. M. (2018). Which taxa are alien? Criteria, applications, and uncertainties. *BioScience*, 68, 496–509. https://doi.org/10.1093/biosci/biy057

Feeley, K. J. (2015). Moving forward with species distributions. *American Journal of Botany*, 102, 173–175. https://doi.org/10.3732/ajb.1400545

Fielding, A. H., & Bell, J. F. (1997). A review of methods for the assessment of prediction errors in conservation presence/absence models. *Environmental Conservation*, 24, 38–49. https://doi.org/10.1017/S0376892997000088

Fitzpatrick, M. C., & Hargrove, W. W. (2009). The projection of species distribution models and the problem of non-analog climate. *Biodiversity and Conservation*, 18, 2255–2261. https://doi.org/10.1007/s10531-009-9584-8

Forester, B. R., DeChaine, E. G., & Bunn, A. G. (2013). Integrating ensemble species distribution modelling and statistical phylogeography to inform projections of climate change impacts on species distributions. *Diversity and Distributions*, 19, 1480–1495. https://doi.org/10.1111/ddi.12098

Gallien, L., Münkemüller, T., Albert, C. H., Boulangeat, I., & Thuiller, W. (2010). Predicting potential distributions of invasive species: Where to go from here? *Diversity and Distributions*, 16, 331–342. https://doi.org/10.1111/j.1472-4642.2010.00652.x

Gottfried, M., Pauli, H., Futschik, A., Akhalkatsi, M., Barančok, P., Benito Alonso, J. L., Coldea, G., Dick, J., Erschbamer, B., Fernández Calzado, M. R., Kazakis, G., Krajči, J., Larsson, P., Mallaun, M., Michelsen, O., Moiseev, D., Moiseev, P., Molau, U., Merzouki, A., ... Grabherr, G. (2012). Continent-wide response of mountain vegetation to climate change. *Nature Climate Change*, 2, 111–115. https://doi.org/10.1038/nclimate1329

Guan, B.-C., Guo, H.-J., Chen, S.-S., Li, D.-M., Liu, X., Gong, X. I., & Ge, G. (2020). Shifting ranges of eleven invasive alien plants in China in the face of climate change. *Ecological Informatics*, 55, 101024. https://doi.org/10.1016/j.ecoinf.2019.101024

Gurevitch, J., Scheiner, S. M., & Fox, G. A. (2006). *The ecology of plants*, 2nd ed. Sinauer.

Haeuser, E., Dawson, W., Thuiller, W., Dullinger, S., Block, S., Bossdorf, O., Carboni, M., Conti, L., Dullinger, I., Essl, F., Klonner, G., Moser, D., Münkemüller, T., Parepa, M., Talluto, M. V., Kreft, H., Pergl, J., Pyšek, P., Weigelt, P., ... van Kleunen, M. (2018). European ornamental garden flora as an invasion debt under climate change. *Journal of Applied Ecology*, 55, 2386–2395. https://doi.org/10.1111/1365-2664.13197

Haeuser, E., Dawson, W., & van Kleunen, M. (2017). The effects of climate warming and disturbance on the colonization potential of ornamental alien plant species. *Journal of Ecology*, 105, 1698–1708. https://doi.org/10.1111/1365-2745.12798

Harter, D. E. V., Irl, S. D. H., Seo, B., Steinbauer, M. J., Gillespie, R., Triantis, K. A., Fernández-Palacios, J.-M., & Beierkuhnlein, C. (2015). Impacts of global climate change on the floras of oceanic islands – Projections, implications and current knowledge. *Perspectives in Plant Ecology, Evolution and Systematics*, 17, 160–183. https://doi.org/10.1016/j.ppees.2015.01.003

Heikkinen, R. K., Luoto, M., Araújo, M. B., Virkkala, R., Thuiller, W., & Sykes, M. T. (2006). Methods and uncertainties in bioclimatic envelope modelling under climate change. *Progress in Physical Geography*, 30, 751–777. https://doi.org/10.1177/0309133306071957

Hellmann, J.J., Bierwagen, B. G., Dukes, J. S., & Byers, J. E. (2008). Five potential consequences of climate change for invasive species. *Conservation Biology*, 22, 534–543. https://doi.org/10.1111/j.1523-1739.2008.00951.x

Hengl, T., de Jesus, J. M., MacMillan, R. A., Batjes, N. H., Heuvelink, G. B. M., Ribeiro, E., Samuel-Rosa, A., Kempen, B., Leenaars, J. G. B., Walsh, M. G., & Gonzalez, M. R. (2014). SoilGrids1km – Global Soil Information Based on Automated Mapping. *PLoS One*, 9, e105992. https://doi.org/10.1371/journal.pone.0105992

Hijmans, R. J., van Etten, J., Sumner, M., Cheng, J., Bevan, A., Bivand, R., & Wueest, R. (2019). raster: geographic data analysis and modeling v.2.9-23. R Foundation for Statistical Computing. Retrieved from https://cran.r-project.org/web/packages/raster/index.html
Hirzel, A. H., Hausser, J., Chessel, D., & Perrin, N. (2002). Ecological-niche factor analysis: How to compute habitat-suitability maps without absence data? *Ecology*, *83*, 2027-2036. 10.1890/0012-9658(2002)083[2027:ENFAHT]2.0.CO;2

Hobohm, C. (Ed.) (2014). *Endemism in Vascular Plants. [Plant and Vegetation 9]*. Springer.

Jiménez-Valverde, A., & Lobo, J. M. (2007). Threshold criteria for conversion of probability of species presence to either-or presence-absence. *Acta Oecologica*, *31*, 361-369. https://doi.org/10.1016/j. actao.2007.02.001

Kalusová, V., Chytrý, M., van Kleunen, M., Mucina, L., Dawson, W., Essl, F., Kreft, H., Pergl, J., Weigelt, P., Winter, M., & Pyšek, P. (2017). Naturalization of European plants on other continents: The role of donor habitats. *Proceedings of the National Academy of Sciences*, *114*, 13756-13761. https://doi.org/10.1073/pnas.1705487114

Karger, D. N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W., Zimmermann, N. E., Linder, H. P., & Kessler, M. (2017). Climatologies at high resolution for the earth's land surface areas. *Scientific Data*, *4*, 170122. https://doi.org/10.1038/sdata.2017.122

Knutti, R., & Sedlacek, J. (2013). Robustness and uncertainties in the New CMIP5 climate model projections. *Nature Climate Change*, *3*, 369-373. https://doi.org/10.1038/nclimate1716

Lembrechts, J. J., Pauchard, A., Lenoir, J., Nuñez, M. A., Geron, C., Ven, A., Bravo-Monasterio, P., Teneb, E., Nijs, I., & Milbau, A. (2016). Disturbance is the key to plant invasions in cold environments. *Proceedings of the National Academy of Sciences*, *113*, 14061-14066. https://doi.org/10.1073/pnas.1608980113

Lenoir, J., Bertrand, R., Comte, L., Bourgeaud, L., Hattab, T., Murienne, J., & Grenouillet, G. (2020). Species better track climate warming in the oceans than on land. *Nature Ecology and Evolution*, *4*, 1044-1059. https://doi.org/10.1038/s41559-020-1198-2

Lenoir, J., Gégout, J.-C., Guisan, A., Vittoz, P., Wohlgemuth, T., Zimmermann, N. E., Dullinger, S., Pauli, H., Willner, W., & Svenning, J.-C. (2010). Going against the flow: Potential mechanisms for unexpected downslope range shifts in a warming climate. *Ecography*, *33*, 295-303. https://doi.org/10.1111/j.1600-0587.2010.06279.x

Liu, Y., Oduor, A. M. O., Zhang, Z., Manea, A., Tooth, I. M., Leishman, M. R., Xu, X., & van Kleunen, M. (2017). Do invasive alien plants benefit more from global environmental change than native plants? *Global Change Biology*, *23*, 3363-3370. https://doi.org/10.1111/gcb.13579

MacDougall, A. S., & Turkington, R. (2005). Are invasive species the drivers or passengers of change in degraded ecosystems? *Ecology*, *86*, 42-55. https://doi.org/10.1890/04-0669

Marmion, M., Parviainen, M., Luoto, M., Heikkinen, R. K., & Thuiller, W. (2009). Evaluation of consensus methods in predictive species distribution modelling. *Diversity and Distributions*, *15*, 59-69. https://doi.org/10.1111/j.1472-4642.2008.00491.x

Mauri, A., Strona, G., & San-Miguel-Ayanz, J. (2017). EU-Forest, a high-resolution tree occurrence dataset for Europe. *Scientific Data*, *4*, 160123. https://doi.org/10.1038/sdata.2016.123

Mayer, K., Haeuser, E., Dawson, W., Essl, F., Kreft, H., Pergl, J., Pyšek, P., Weigelt, P., Winter, M., Lenzner, B., & van Kleunen, M. (2017). Naturalization of ornamental plant species in public green spaces and private gardens. *Biological Invasions*, *19*, 3613-3627. https://doi.org/10.1007/s10530-017-1594-y

Meyer, C., Weigelt, P., & Kreft, H. (2016). Multidimensional biases, gaps and uncertainties in global plant occurrence information. *Ecology Letters*, *19*, 992-1006. https://doi.org/10.1111/ele.12624

Mooney, H. A., & R. J. Hobbs (Eds.) (2000). *Invasive species in a changing world*. Island Press.

Nakagawa, S., & Schielzeth, H. (2013). A general and simple method for obtaining R² from generalized linear mixed-effects models. *Methods in Ecology and Evolution*, *4*, 133-142.

Novoa, A., Kumschick, S., Richardson, D. M., Rouget, M., & Wilson, J. R. U. (2016). Native range size and growth form in Cactaceae

predict invasiveness and impact. *Neobiota*, *30*, 75-90. https://doi.org/10.3897/neobiota.30.7253

Oliver, T. H., & Morecroft, M. D. (2014). Interactions between climate change and land use change on biodiversity: Attribution problems, risks, and opportunities. *Wires Climate Change*, *5*, 317-335.

Paradis, E., Blomberg, S., Bolker, B., Brown, J., Claramunt, S., Claude, J., de Vienne, D. (2020). ape: Analyses of Phylogenetics and Evolution v.5.4-1. R Foundation for Statistical Computing. Retrieved from https://cran.r-project.org/web/packages/ape/index.html

Pearman, P. B., Guisan, A., Broennimann, O., & Randin, C. F. (2008). Niche dynamics in space and time. *Trends in Ecology & Evolution*, *23*, 149-158. https://doi.org/10.1016/j.tree.2007.11.005

Pearson, R. G., Phillips, S. J., Loranty, M. M., Beck, P. S. A., Damoulas, D., Knight, S. J., & Goetz, S. J. (2013). Shifts in Arctic vegetation and associated feedbacks under climate change. *Nature Climate Change*, *3*, 673-677. https://doi.org/10.1038/nclimate1858

Pouteau, R., Biurrun, I., Brunel, C., Chytrý, M., Dawson, W., Essl, F., ..., & van Kleunen, M. (2021). Data from: Global maps of current (1979-2013) and future (2061-2080) habitat suitability probability for 1,485 European endemic plant species. *Dryad Digital Repository*. Retrieved from https://datadryad.org/stash/dataset/doi:10.5061/dryad.qv9s4mwf3

Pouteau, R., Thuiller, W., Hobohm, C., Brunel, C., Conn, B. J., Dawson, W., Sá Dechoum M., Ebel A. L., Essl F., Fragman-Sapir O., Fristoe T., Jogan N., Kreft H., Lenzner B., Meyer C., Pergl J., Pyšek P., Verkhozina A., Weigelt P., ..., van Kleunen, M. (2021). Climate and socio-economic factors explain differences between observed and expected naturalization patterns of European plants around the world. *Global Ecology and Biogeography*, *30*, 1514-1531. http://dx.doi.org/10.1111/geb.13316

Prinzing, A., Durka, W., Klotz, S., & Brandl, R. (2002). Which species become aliens? *Evolutionary Ecology Research*, *4*, 385-405.

Pyšek, P., Guo, W.-Y., Štajerová, K., Moora, M., Bueno, C. G., Dawson, W., Essl, F., Gerz, M., Kreft, H., Pergl, J., van Kleunen, M., Weigelt, P., Winter, M., & Zobel, M. (2019). Facultative mycorrhizal associations promote plant naturalization worldwide. *Ecosphere*, *10*, e02937. https://doi.org/10.1002/ecs2.2937

Pyšek, P., Jarošík, V., Pergl, J., Randall, R., Chytrý, M., Kühn, I., Tichý, L., Danihelka, J., Chrtek jun, J., & Sádlo, J. (2009). The global invasion success of Central European plants is related to distribution characteristics in their native range and species traits. *Diversity and Distributions*, *15*, 891-903. https://doi.org/10.1111/j.1472-4642.2009.00602.x

Pyšek, P., Manceur, A. M., Alba, C., McGregor, K. F., Pergl, J., Štajerová, K., Chytrý, M., Danihelka, J., Kartesz, J., Klimešová, J., Lučanová, M., Moravcová, L., Nishino, M., Sádlo, J., Suda, J., Tichý, L., & Kühn, I. (2015). Naturalization of central European plants in North America: Species traits, habitats, propagule pressure, residence time. *Ecology*, *96*, 762-774. https://doi.org/10.1890/14-1005.1

Pyšek, P., Pergl, J., Essl, F., Lenzner, B., Dawson, W., Kreft, H., Weigelt, P., Winter, M., Kartesz, J., Nishino, M., Antonova, L. A., Barcelona, J. F., Cabesaz, F. J., Cárdenas, D., Cárdenas-Toro, J., Castaño, N., Chacón, E., Chatelain, C., Dullinger, S., ..., van Kleunen, M. (2017). Naturalized alien flora of the world: Species diversity, taxonomic and phylogenetic patterns, geographic distribution and global hotspots of plant invasion. *Preslia*, *89*, 203-274. https://doi.org/10.23855/preslia.2017.203

Pyšek, P., Richardson, D. M., Rejmánek, M., Webster, G., Williamson, M., & Kirschner, J. (2004). Alien plants in checklists and floras: Towards better communication between taxonomists and ecologists. *Taxon*, *53*, 131-143. https://doi.org/10.2307/4135498

Pyšek, P., Richardson, D. M., & Williamson, M. (2004). Predicting and explaining plant invasions through analysis of source area floras: Some critical considerations. *Diversity and Distributions*, *10*, 179-187. https://doi.org/10.1111/j.1366-9516.2004.00079.x
Pyšek, P., Sádlo, J., Mandák, B., & Jarošík, V. (2003). Czech alien flora and the historical pattern of its formation: What came first to Central Europe? *Oecologia*, 135, 122-130. https://doi.org/10.1007/s0044 2-002-1170-7

Rejmánek, M. (1996). A theory of seed plant invasiveness: The first sketch. *Biological Conservation*, 78, 171-181. https://doi. org/10.1016/0006-3207(96)00026-2

Seebens, H., Blackburn, T. M., Dyer, E. E., Genovesi, P., Hulme, P. E., Jeschke, J. M., Pagad, S., Pyšek, P., van Kleunen, M., Winter, M., Ansong, M., Arianoutsou, M., Bacher, S., Blasius, B., Brockerhoff, E. G., Brundu, G., Capinha, C., Causton, C. E., Celesti-Grapow, L., ... Essl, F. (2018). The global rise in emerging alien species results from increased accessibility of new source pools. *Proceedings of the National Academy of Sciences*, 115, E2264-E2273. https://doi.org/10.1073/ pnas.1719429115

Seebens, H., Blackburn, T. M., Dyer, E. E., Genovesi, P., Hulme, P. E., Jeschke, J. M., Pagad, S., Pyšek, P., Winter, M., Arianoutsou, M., Bacher, S., Blasius, B., Brundu, G., Capinha, C., Celesti-Grapow, L., Dawson, W., Dullinger, S., Fuentes, N., Jäger, H., ... Essl, F. (2017). No saturation in the accumulation of alien species worldwide. *Nature Communications*, 8, 14435. https://doi.org/10.1038/ncomms14435

Stephenson, N. L., & Das, A. J. (2011). Comment on "Changes in climatic water balance drive downhill shifts in plant species' optimum elevations". *Science*, 331, 177. https://doi.org/10.1126/science.1205740

Stohlgren, T. J., Ma, P., Kumar, S., Rocca, M., Morisette, J. T., Jarnevich, C. S., & Benson, N. (2010). Ensemble habitat mapping of invasive plant species. *Risk Analysis*, 30, 224-235. https://doi. org/10.1111/j.1539-6924.2009.01343.x

Stralberg, D., Jongsomjit, D., Howell, C. A., Snyder, M. A., Alexander, J. D., Wiens, J. A., & Root, T. L. (2009). Re-shuffling of species with climate disruption: A no-analog future for California birds? *PLoS One*, 4, e6825. https://doi.org/10.1371/journal.pone.0006825

Thuiller, W., Gassó, N., Pino, J., & Vilà, M. (2012). Ecological niche and species traits: Key drivers of regional plant invader assemblages. *Biological Invasions*, 14, 1963-1980. https://doi.org/10.1007/s1053 0-012-0206-0

Thuiller, W., Lafourcade, B., Engler, R., & Araújo, M. B. (2009). BIOMOD - a platform for ensemble forecasting of species distributions. *Ecography*, 32, 369-373. https://doi.org/10.1111/j.1600-0587.2008.05742.x

Thuiller, W., Lavorel, S., & Araújo, M. B. (2005). Niche properties and geographical extent as predictors of species sensitivity to climate change. *Global Ecology and Biogeography*, 14, 347-357. https://doi. org/10.1111/j.1466-822X.2005.00162.x

van Kleunen, M., Dawson, W., Essl, F., Pergl, J., Winter, M., Weber, E., Kreft, H., Weigelt, P., Kartesz, J., Nishino, M., Antonova, L. A., Barcelona, J. F., Cabezas, F. J., Cárdenas, D., Cárdenas-Toro, J., Castaño, N., Chacón, E., Chatelain, C., Ebel, A. L., ... Pyšek, P. (2015). Global exchange and accumulation of non-native plants. *Nature*, 255, 100-106. https://doi.org/10.1038/nature14910

van Kleunen, M., Johnson, S. D., & Fischer, M. (2007). Predicting naturalization of southern African Iridaceae in other regions. *Journal of Applied Ecology*, 44, 594-603. https://doi.org/10.1111/j.1365-2664.2007.01304.x

van Kleunen, M., Pyšek, P., Dawson, W., Essl, F., Kreft, H., Pergl, J., ... & Winter, M. (2019). The Global Naturalized Alien Flora (GloNAF) database. *Ecology*, 100, e02542.

van Kleunen, M., Xu, X., Yang, Q., Maurel, N., Zhang, Z., Dawson, W., Essl, F., Kreft, H., Pergl, J., Pyšek, P., Weigelt, P., Moser, D., Lenzner, B., & Fristoe, T. S. (2020). Economic use of plants is key to their naturalization success. *Nature Communications*, 11, 3201. https://doi. org/10.1038/s41467-020-16982-3

van Proosdijl, A. S. J., Sosef, M. S. M., Wieringa, J. J., & Raes, N. (2016). Minimum required number of specimen records to develop accurate

species distribution models. *Ecography*, 39, 542-552. https://doi. org/10.1111/ecog.01509

Violle, C., Choler, P., Borgy, B., Garnier, E., Amiaud, B., Debarros, G., Diquelouel, S., Gachet, S., Jolivet, C., Kattge, J., Lavorel, S., Lemauviel-Lavenant, S., Loranger, J., Mikolajczak, A., Munoz, F., Olivier, J., & Viovy, N. (2015). Vegetation ecology meets ecosystem science: Permanent grasslands as a functional biogeography case study. *Science of the Total Environment*, 534, 43-51. https://doi. org/10.1016/j.scitotenv.2015.03.141

Walther, G.-R., Roques, A., Hulme, P. E., Sykes, M. T., Pyšek, P., Kühn, I., Zobel, M., Bacher, S., Botta-Dukát, Z., & Bugmann, H. (2009). Alien species in a warmer world: Risks and opportunities. *Trends in Ecology & Evolution*, 24, 686-693. https://doi.org/10.1016/j.tree.2009.06.008

Williams, J. W., & Jackson, S. T. (2007). Novel climates, no-analog communities, and ecological surprises. *Frontiers in Ecology and the Environment*, 5, 475-482. https://doi.org/10.1890/070037

Zimmermann, N. E., Yoccoz, N. G., Edwards, T. C., Meier, E. S., Thuiller, W., Guisan, A., Schmatz, D. R., & Pearman, P. B. (2009). Climatic extremes improve predictions of spatial patterns of tree species. *Proceedings of the National Academy of Sciences USA*, 106, 19723-19728. https://doi. org/10.1073/pnas.0901643106

Zurell, D., Franklin, J., König, C., Bouchet, P. J., Serra-Diaz, J. M., Dormann, C. F., & Merow, C. (2020). A standard protocol for describing species distribution models. *Ecography*, 43, 1261-1277.

## BIOSKETCH

Robin Pouteau is a plant ecologist at IRD (French Research Institute for Sustainable Development) with a strong focus on the impact of biological invasions on biodiversity. This project is the result of a collaboration with two consortia of international researchers working on plant inventories: Global Naturalized Alien Flora (GloNAF) and European Vegetation Archive (EVA).

Author contributions: R.P. and M.v.K. conceived the idea for this manuscript with input from W.T. All authors provided the data, R.P. performed the analysis and wrote the first draft of the manuscript with help from M.v.K., and all authors contributed substantially to revisions.

## SUPPORTING INFORMATION

Additional supporting information may be found online in the Supporting Information section.

**How to cite this article:** Pouteau, R., Biurrun, I., Brunel, C., Chytrý, M., Dawson, W., Essl, F., Fristoe, T., Haveman, R., Hobohm, C., Jansen, F., Kreft, H., Lenoir, J., Lenzner, B., Meyer, C., Moeslund, J. E., Pergl, J., Pyšek, P., Svenning, J.-C., Thuiller, W., ... van Kleunen, M. (2021). Potential alien ranges of European plants will shrink in the future, but less so for already naturalized than for not yet naturalized species. *Diversity and Distributions*, 00, 1-14. https://doi.org/10.1111/ ddi.13378