# Assessing the impacts of land use and climate change on the distribution patterns of Ulex europaeus L. (Fabaceae) in the Canary Islands

Daniele da Re, Enrico Tordoni, Agustín Naranjo-Cigala, Miguel Antonio Padrón-Mederos, Maya González, Cristina González-Montelongo, José Ramón Arévalo-Sierra

► To cite this version:

Daniele da Re, Enrico Tordoni, Agustín Naranjo-Cigala, Miguel Antonio Padrón-Mederos, Maya González, et al.. Assessing the impacts of land use and climate change on the distribution patterns of Ulex europaeus L. (Fabaceae) in the Canary Islands. Biological Invasions, 2024, 10.1007/s10530-024-03452-w. hal-04781903

HAL Id: hal-04781903

https://hal.inrae.fr/hal-04781903v1

Submitted on 14 Nov 2024

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_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Assessing the impacts of land use and climate change on the distribution patterns of *Ulex europaeus* L. (Fabaceae) in the Canary Islands

Daniele Da Re* · Enrico Tordoni · Agustín Naranjo-Cigala ·

Miguel Antonio Padrón-Mederos · Maya González ·

Cristina González-Montelongo · José Ramón Arévalo-Sierra

Received: 18 July 2024 / Accepted: 16 September 2024

© The Author(s) 2024

**Abstract** Biological invasions are one of the major threats to biodiversity, but their impact is particularly detrimental on oceanic islands like the Canary Archipelago. The common gorse (*Ulex europaeus* L. (Fabaceae)) is a highly invasive shrub with established populations in Tenerife, the sole island of the archipelago where it is present. Understanding the habitat preferences of *U. europaeus* is essential for predicting its current and potential future distribution across Tenerife and other Canary Islands, guiding effective local management practices. In 2019 and 2020, we surveyed different populations of *U. europaeus* in Tenerife, retrieving information on its

abundance, presence of other invasive species and most frequent natural and anthropogenic characteristics of the landscape. We used this information to build explanatory and predictive models to identify the key natural and anthropogenic drivers of *U. europaeus* abundance in Tenerife and estimate the potential distribution of the species across the whole archipelago under current and future climatic conditions. Our findings showed that *U. europaeus* thrives in humid areas impacted by human activities where other invasive species persist. Both current and future climatic conditions do not support the presence of the species in the more arid islands of the archipelago (i.e., Fuerteventura and Lanzarote), rather highlight that the windwards, and thus more humid, areas of the other islands might support the species also

**Supplementary Information** The online version contains supplementary material available at https://doi.org/10.1007/s10530-024-03452-w.

D. Da Re (✉)
Center Agriculture Food Environment, University of Trento, San Michele All'Adige, Italy
e-mail: daniele.dare@unitn.it

D. Da Re
Applied Ecology Unit, Edmund Mach Foundation, San Michele All'Adige, Italy

E. Tordoni
Institute of Ecology and Earth Science, University of Tartu, Tartu, Estonia

A. Naranjo-Cigala
Department of Geography, University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain
e-mail: agustin.naranjo@ulpgc.es

M. A. Padrón-Mederos · C. González-Montelongo ·
J. R. Arévalo-Sierra
Department of Botany, Ecology and Plant Physiology, University of La Laguna, San Cristobal de La Laguna, Spain
e-mail: jarevalo@ull.edu.es

M. A. Padrón-Mederos
Jardín de Aclimatación de La Orotava (ICIA), Puerto de La Cruz, Spain

M. González
INRAE, Bordeaux Sciences Agro, UMR 1391 ISPA, 33882 Villenave-d'Ornon, France
under future warmer climatic scenarios. These find-
ings deepen our understanding of *U. europaeus* local
dynamics and are crucial to inform targeted man-
agement strategies to mitigate its impact across the
Canary Archipelago and, ultimately, oceanic islands.

**Keywords** Biological invasions · Climate change · Common gorse · Machine learning Oceanic islands

**Introduction**

Biological invasions are one of the main drivers of habitat degradation and species loss (Bellard et al. 2016; IPBES 2023). This threat is particularly pronounced on oceanic islands (Donlan and Wilcox 2008; Kueffer et al. 2010), where their inherent remoteness fostered the evolutionary isolation of native communities, leaving them particularly susceptible to invasive alien species—IAS (Hulme 2009; Silva and Smith 2004; Pauchard et al. 2009; Moser et al. 2018). Human activities, including globalisation and land cover/land use change, have emerged as the major forces driving the proliferation of IAS that often lead to a taxonomic and functional homogenisation of insular biotas (Levine and d'Antonio 2003; Westphal et al. 2008; Pysek et al. 2010; Tordoni et al. 2019; Caro et al. 2022). Unfortunately, the Canary Islands (Spain) are no exception to this trend (Atkinson and Cameron 1993; Arévalo et al. 2005; 2010; Bacaro et al. 2015). Conserving biodiversity on oceanic islands is crucial due to their unique ecosystems and isolation, which often results in high levels of endemism representing hotspots for evolution (Whitaker and Fernández-Palacios 2007). Without conservation efforts and IAS management practices, the delicate balance of these insular ecosystems could be disrupted, leading to irreversible loss of species and ecological functions (Kier et al. 2009).

*Ulex europaeus* L. (Fabaceae), commonly known
as the common gorse, is one of the most invasive
shrubs in the world, having been associated with
displacing native species and the homogenisation of
ecosystems in areas where it has been established
(León Cordero et al. 2016; Galappaththi et al. 2023).
The impact of *U. europaeus* on the native flora of the
Canary archipelago was evident with studies reveal-
ing its dispersal along the northern regions of Ten-
erife, the only island of the archipelago where the

species is currently naturalised (García-Gallo et al. 1989, 2008). The species was presumably introduced multiple times on the island: though the first observation dates back to the nineteenth century (Buch 1825), most of the introductions likely happened during the 1960s, coinciding with the importation of trees from the Iberian Peninsula for reforestation purposes (Sanz et al. 2004; Morente-López et al. 2023), primarily *Pinus radiata* or *Eucalyptus* spp. (see Marrero 2016 concerning Gran Canaria).

Human-induced land use change is considered one
of the main drivers of the expansion of *U. europaeus*,
a pioneer and shade intolerant species, given its pro-
pensity to colonise abandoned agricultural regions
(Elorza et al. 2004; Muthulingam and Marambe
2022). The Canary Islands government estimates
that about 60% of agricultural land in the archipelago
has been left fallow in recent decades (Gobierno de
Canarias 2023), making it susceptible to colonisa-
tion by opportunistic invaders (Benning et al. 2002;
Mosher et al. 2009; Essl et al. 2020; Roberts and
Florentine 2021). In the case of Tenerife Island, there
are no documented uses of the species for agriculture
(Sanz et al. 2004), though its application for compost,
fodder and hedge plant has been reported in the rural
areas of the island (Álvarez Escobar 2011; oral com-
munications collected by M.A. Padrón-Mederos). If
human-driven land use change can favour the expan-
sion of *U. europaeus* in the Canary Islands, global
warming might likely limit it. Despite its ability to
tolerate warm periods, *U. europaeus* typically thrives
in cooler and rainy areas (Roberts and Florentine
2021), indicating potential challenges for the spe-
cies in adapting to future climate conditions. Over
the past seven decades, the Canary Archipelago has
observed an upward shift in temperature values, with
an increase of approximately 0.6 °C in mean tempera-
ture, with minimum night temperatures alarmingly
increased by almost 1.5 °C (Martín et al. 2012).

The impacts of land use change and global warm-
ing and their interaction can yield different and some-
times contrasting outcomes for this species, compli-
cating the design of effective management strategies.
Numerous studies have explored the primary factors
influencing the distribution of *U. europaeus* over
large geographical scales (Hernández-Lambraño et al.
2017; Christina et al. 2020; Roberts and Florentine
2021; Ángel-Vallejo et al. 2024), however, effec-
tive management practices necessitate a finer-scale
understanding of the species' ecology. Therefore, it is crucial to evaluate the predominant anthropogenic and natural drivers of *U. europaeus* in Tenerife Island and subsequently, to anticipate dispersion trajectories, assessing which areas of Tenerife, as well as other islands within the Canary Archipelago, may be susceptible to invasion. In addition, we can speculate that patterns of co-occurrence with other IAS can reflect similar introduction pathways or shared ecological properties (Kuebbing and Nuñez 2015), and may involve physical modifications in the soil which, in turn, might promote future invasions (Vujanović et al. 2022). In literature, the interaction among IAS has been detected to be mostly negative or neutral (Kuebbing and Nuñez 2015; Lortie et al. 2021), and resulted in further complicate management and restoration activities due to the interacting effects of co-occurring invaders (Zenni et al. 2020).

In this study, we surveyed different populations of *U. europaeus* located on Tenerife Island, collecting information about the abundance of the species, the land use, and the presence of other invasive species. We aimed to answer the following questions employing machine learning and classic statistical approaches:

1. What are the main natural and human-related factors influencing the abundance of *Ulex europaeus* on Tenerife Island?

2. Are other invasive plant species associated with the abundance of *U. europaeus*?

3. What is the potential habitat distribution of the species in Tenerife and the other islands of the Canary Archipelago under the current and future climatic scenarios?

We attempted to answer these questions to deepen our understanding of *U. europaeus* local dynamics, which are crucial to inform targeted management strategies to mitigate its impact across the Canary Archipelago and, ultimately, oceanic islands.

## Methods

### Species ecology

*Ulex europaeus* is an invasive, evergreen and highly plastic shrub listed as one of the most invasive species

in the world (Altamirano et al. 2016; Broadfield and McHenry 2019). This species has been introduced in different parts of the world since the nineteenth century (Australia, New Zealand, South America, California, and South Africa, among other regions) and is now distributed from equatorial to temperate regions (POWO 2023).

*Ulex europaeus* has a low-temperature tolerance limit and cannot withstand severe and prolonged freezing temperatures (Atlan and Udo 2019; Christina et al. 2020). Therefore, it is typically found in areas where monthly temperatures average above zero, though it has colonised coastal areas at higher latitudes in Europe and in the Americas (Clements et al. 2001; Ángel-Vallejo et al. 2024). Concerning precipitation, the species prefers regions with moderate to high annual rainfall (e.g. between 500 to 1500 mm/year; Broadfield and McHenry 2019), as adequate moisture availability during the growing season is crucial for its survival and growth. Despite its preference for moderate to high rainfall, *U. europaeus* is well-adapted to tolerate dry and drought conditions during the summer months. It can withstand periods of water scarcity due to its deep root system and water-conserving adaptations like spiny leaves and taproot (Christina et al. 2023).

In Tenerife, flowers and seeds of *U. europaeus* can be found throughout the year (although more abundant in January–February), and seed germination is strongly stimulated by fire, as occurred with the wildfire of 2007 on the north side of the island (Christina et al. 2023). In its non-native range, *U. europaeus* spread is fostered not just by fires, but also by the high species reproductive fitness, a long vegetative period, prolonged seed longevity and rapid growth and the absence of native competitor (Kariyawasam and Ratnayake 2019). The dispersion of *U. europaeus* alters soil and landscape dynamics in areas of major invasion, inhibiting the growth of agricultural and native species, creating shelter for pest species and reducing the richness of competing species at a site, all of which contribute to the economic and environmental degradation of the land (Altamirano et al. 2016; Udo et al. 2018). In addition, *U. europaeus* reduces soil fertility through the depletion of nutrients (Bateman and Vitousek 2018) or promotes vegetation flammability becoming a management fire control problem in these invaded areas (Atlan and Limbada, 2019). Because of that, the invasion by *U. europaeus* has
changed the native habitat on the island of Tenerife and is preventing the regeneration of native plant communities on abandoned fields (personal communication of J Arévalo Sierra and A Naranjo-Cigala).

## Sampling design

The Biodiversity Database of the Canary Islands (BDCI; Gobierno de Canarias 2024) is the official taxonomic record for the archipelago, containing information on the list and known distribution of plants, fungi, animals, and other living organisms in the Canary Islands and their waters (https://www.biodiversidadcanarias.es/biota/). The BDCI records the species occurrences using a 500 m spatial resolution grid covering the entire Archipelago. According to the BDCI (accessed in 2019, before the fieldwork activities), *U. europaeus* had two main populations on Tenerife Island. The first is located near the Macizo de Anaga, northeast of the island, and covers approximately 4.25 km². The second one, located in the northwest part of the island, covers approximately 66.5 km² (Fig. 1).

Starting from these known locations, during January–March 2020 and 2021, we surveyed each grid cell where the BDCI reported a *U. europaeus* occurrence. Furthermore, we systematically examined the eight adjacent cells surrounding each grid cell with a confirmed occurrence. If the species

was detected in any of these neighbouring cells, the sampling scope was expanded to include additional neighbouring cells. Following the methodology adopted in several vegetation surveys conducted on the island (Panareda and Nuet 1981; Panareda 2000; Naranjo-Cigala et al. 2009; 2016; 2017; Arévalo et al. 2010), we recorded the relative abundance of the species (see the abundance class definition in Table SM1.1), as well as the dominant geomorphological characteristics (plateau, hill, bottom of ravines, lava flow, or badland - from Spanish *malpaís* -), and main human land uses, indicating whether the area was an abandoned field, bordering a trail, or terraced (Table SM1.2). The level of anthropisation (low, medium or high) was recorded following a semiquantitative scale described in Arévalo et al. (2005) to determine the level of anthropisation (Table SM1.2). Furthermore, accessibility information was documented, detailing whether the site was reachable via trails or roads and specifying the level of ease of access (< 100 m from a trail or road), low difficulty (< 500 m), or high difficulty (> 500 m). Finally, the presence of other invasive species was noted, according to the chorological status adopted in the BDCI (Gobierno de Canarias 2024), except in several cases where the chorological status is uncertain (e.g. *Pteridum aquilinum*).

A

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

B

<figure><img src="image_3.png" /><figcaption>**Fig. 1** a Location of the Canary Archipelago with respect to Europe and portion of Tenerife Island surveyed (in red); b Location of the populations of *Ulex europaeus* in Tenerife Island according to the BDCI (accessed in 2019, before the fieldwork)</figcaption></figure>

<figure><img src="image_4.png" /></figure>
## Data analysis

This section provides a concise overview of the methodologies employed to address the diverse questions posed in the introduction. This includes outlining the specific approaches and techniques utilised to investigate the relationships of the species with anthropogenic features, assessing the role of the species within the vegetation community, and delving into its current and future habitat range dynamics.

### What are the main natural and human-related factors influencing the abundance of *U. europaeus* on Tenerife Island?

We used a Random Forest (RF) model to investigate how the different natural and anthropogenic factors present in the surveyed areas of Tenerife Island influence the species' abundance. Random Forest is a machine learning method widely used for classification and regression tasks (Breiman 2001; Liaw and Wiener 2002). It combines multiple decision trees, each trained on random subsets of the data and features (i.e., predictor variables) through a process called bootstrap aggregation, whose individual predictions are combined through a majority vote (classification) or averaging (regression). Random Forest has been widely applied in ecological studies (e.g., Evans, et al. 2010; Guisan et al. 2017; Rodríguez-Alarcón et al. 2024) and is known for its flexibility and robustness.

We investigated the effect of the natural and anthropogenic variables collected during the fieldwork (dominant geomorphological features, human land uses, road density and accessibility; n=23, Table SM1.2) on the categorised abundance of *U. europaeus*. We performed a variable selection procedure using the Boruta algorithm (Kursa and Rudnicki 2010) to build a parsimonious model including non-correlated variables. Boruta is a feature selection method used in machine learning to identify the most relevant variables for predictive modelling. It operates by comparing the importance of each predictor variable against randomised versions of itself, measuring its significance to random noise. Variables deemed significantly more important than their random counterparts are considered relevant and retained for further analysis, while those deemed less important are discarded. Finally, the hyperparameters

of the RF model were tuned using a grid search in the parameter space and a tenfold cross-validation procedure with 3 repetitions using the R package 'caret' (Kuhn 2008). The observations were partitioned with 80% used for training the model and 20% for testing. The classification accuracy of the model was assessed on the test dataset using sensitivity and specificity metrics derived from a confusion matrix, which compares predicted and actual class labels (for more details about the data partitioning and hyperparameter tuning see SM2).

As with other machine learning algorithms, one of the notable drawbacks of RF is its perceived lack of explicability, often rendering it like a black box. Recent developments introduce explainable artificial intelligence (xAI), a set of methods designed to enhance the interpretability of machine learning predictions (Ryo et al. 2021; Pichler and Hartig 2023). In particular, we used the variable importance and Shapley's values (Lundberg and Lee 2017) to interpret the relative importance of the different variables contributing to the abundance of *U. europaeus*. Variable importance refers to the measure of the contribution of each predictive variable (feature) in the predictive performance of the model. Random forest uses an ensemble of decision trees, and variable importance is determined by assessing how much each variable decreases the accuracy of the model when it is randomly permuted while keeping other variables constant. The greater the decrease in accuracy, the more important the variable is considered. Shapley's value is a concept from cooperative game theory that, in the machine learning context, assigns a fair and unique contribution value to each variable based on its marginal impact across all possible combinations of variables.

### Are other invasive plant species associated with the abundance of *U. europaeus*?

We conducted a co-occurrence analysis to examine the associations between *U. europaeus* and other IAS observed in the field. This analysis aimed to determine whether strong co-occurrence patterns with *U. europaeus* indicate that these species share similar ecological features. Specifically, we calculated pairwise co-occurrence patterns from the community dataset using the R package 'cooccur' (Griffith et al. 2016). This algorithm uses the probabilistic
model developed by Veech (2013) to evaluate if the
observed co-occurrence patterns deviate from the one
expected by chance. Positive values indicate a high
probability that two taxa co-occur and vice versa. Co-
occurrence values around 0 indicate random patterns.
Co-occurrence matrices were calculated both con-
sidering all abundance classes together than for each
class, independently.

*What is the potential distribution of U. europaeus in Tenerife and the other islands of the Canary Archipelago under the current and future climatic scenarios?*

Correlative species distribution models (SDMs) are valuable tools used in ecology and conservation biology to predict the spatial distribution of species across a specific geographic area (Elith and Leathwick 2009; Guisan and Thuiller 2005; Guisan et al. 2017; Da Re et al. 2023). These models integrate environmental variables, such as temperature, precipitation, and land cover, with known species occurrence or abundance observations to estimate the areas where a species is likely to occur. SDMs have been extensively used in biodiversity conservation and invasive species monitoring (e.g., Da Re et al. 2019; 2020; Romero et al. 2021), as they can provide estimates of the potential spread of invasive species in new environments, providing an effective tool to develop proactive strategies to prevent further spread and control their impact on native ecosystems.

We used an RF model to investigate how different
abiotic variables contribute to the abundance of the
species on Tenerife Island. We selected eight abiotic
variables based on the known ecology of the species,
namely BIO5: Maximum Temperature of Warm-
est Month, BIO6: Minimum Temperature of Coldest
Month, BIO8: Mean Temperature of Wettest Quarter,
BIO9: Mean Temperature of Driest Quarter, BIO13:
Precipitation of Wettest Month, BIO14: Precipita-
tion of Driest Month, BIO16: Precipitation of Wet-
test Quarter, BIO17: Precipitation of Driest Quarter
(Table SM1.3), from the CanaryClim dataset. Canar-
yClim v1.0 (Patiño et al. 2023) is a climate dataset
created by downscaling the global climate model of
CHELSA v1.2 (Karger et al. 2017) to 100 m spatial
resolution, ensuring a finer representation of the mes-
oclimate of the Archipelago. The dataset spans two
time periods: the near-present (1979–2013) and the

late-century (2071–2100), the latest including future
climate scenarios based on various warming shared
socio-economic pathways (SSPs) within the Sixth
Assessment Report of the Intergovernmental Panel
on Climate Change (https://www.ipcc.ch/report/ar6/
wg1/#TS).

Also in this case we performed a variable selec-
tion procedure using the Boruta algorithm, the data
partitioning and the hyperparameter tuning using the
same settings already described in section "What are
the main natural and human-related factors influenc-
ing the abundance of Ulex. europaeus on Tenerife
Island?". Likewise, the classification accuracy of the
model was evaluated using a confusion matrix and
calculating sensitivity and specificity metrics for each
abundance class. We interpreted the relative impor-
tance of the different abiotic variables contributing to
explaining the abundance of *U. europaeus* computing
the variable importance and Shapley's values.

To project the potential dispersion of the species
under different climatic scenarios, we extrapolated
the model predictions, originally trained on Tener-
ife Island, to encompass the other islands within the
archipelago under current and future climatic condi-
tions. We used three different future scenarios char-
acterised by varying levels of sustainability. SSP126
represents a high sustainability pathway with strong
climate action and significant mitigation efforts,
resulting in lower greenhouse gas emissions and a
relatively modest increase in global temperatures.
SSP370 reflects a medium sustainability pathway
with some climate mitigation efforts but still rela-
tively high emissions, leading to more pronounced
temperature increases compared to SSP126. SSP585
denotes a low sustainability pathway and is consid-
ered the "business-as-usual" scenario, characterised
by minimal climate action and high emissions, result-
ing in the most severe temperature increases among
the scenarios.

We assessed the climatic dissimilarity of the study
area in future scenarios compared to current condi-
tions using the multivariate environmental similarity
surfaces (MESS) index (Elith et al. 2010) to mitigate
extrapolation concerns (see Chapt. 17 in Guisan et al.
2017). The MESS index gauges the similarity of envi-
ronmental conditions at each pixel to those observed
in the training data. A positive MESS value signifies
that conditions at that pixel fall within the range of
those observed in the training data, indicating reliable
extrapolation. Conversely, a negative MESS value suggests that conditions at that pixel lie outside the range of the training data, potentially signifying unreliable extrapolation and advising caution in interpreting model predictions in those regions.

## Results

Out of the total 8519 grid cells covering Tenerife Island, 1095 quadrats were examined and 301 showed the presence of *U. europaeus* with varying degrees of abundance/cover: Class0 (absence) with 794 observations, Class1 (1 to 10 specimens) with 50 observations, Class2 (10–49 specimens) with 45 observations, Class3 (50–99 specimens) with 49 observations, Class4 (100–199 specimens) with 40 observations and Class5 (> 200 specimens) with 117 observations (Tab SM1.1).

Our survey allowed identify three main populations of the species in Tenerife Island: the fieldwork confirmed the presence of the species in the Macizo

de Anaga (northeast part of the island), and better defined the two populations located in the northwest (Fig. 2). During the sampling, 45 additional plant-invasive species were recorded (Table SM3.1).

Natural and human-related factors influencing the abundance of *U. europaeus* on Tenerife Island

The variable selection performed with the Boruta algorithm discarded the percentage cover of flat areas as an informative variable. Following the hyperparameter tuning, the minimum node size was set equal to 9 and the mtry equal to 2, resulting in an overall model classification accuracy of 0.9297 (95% CI 0.9129, 0.9441; Table S3.4). Both the variable importance and the global mean Shapley values highlight the access to roads and different levels of anthropic pressure as the most important variables driving the abundance of *U. europaeus* on Tenerife (Fig. 3a, b); this pattern is also relevant across different abundance classes (Fig. 3c).

<figure><img src="image_5.png" /><figcaption>**Fig. 2** Relative abundance of *Ulex europaeus* resulting from the fieldwork conducted in 2020–2021</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Fig. 3** Results of the Random Forest model assessing the natural and human-related factors influencing the abundance of *U. europaeus* on Tenerife Island: a Variable importance, b Global average Shapley value, c Shapley's values broken down for the</figcaption></figure>

different abundance categories. Class1 (1 to 10 specimens); Class2 (10–49 specimens); Class3 (50–99 specimens); Class4 (100–199 specimens); and Class5 (> 200 specimens)

Other invasive plant species associated with the abundance of *U. europaeus* on Tenerife Island

Co-occurrence patterns were estimated in 16.3% of species pair combinations (the others were removed since expected co-occurrence was <1). Of this, we detected higher levels of positive ecological associations, especially for classes 3 and 5 (Fig. 4; Table S3.2). Most of these associations occurred with Ageratina adenophora (Spreng.) R.M.King and H.Rob. (Asteraceae) (Aga), *Pteridium aquilinum* (L.) Kuhn (Dennstaedtiaceae) (Pa), *Chasmanthe floribunda* (Salisb.) N.E.Br. (Iridaceae); and *Opuntia* sp. (Cactaceae) (Osp). Notably, when considering all classes pooled (Fig. 4f), all the associations with the other IAS in Tenerife Island were never different from random expectations.

Current and future distribution of *U. europaeus* in the Canary Islands

The Boruta algorithm, used for variable selection, retained all the selected abiotic variables. Subsequent

hyperparameter tuning established a minimum node size of 6 and a mtry value of 2, yielding an overall model classification accuracy of 0.68 (95% CI 0.61, 0.74; Table S3.4). Among these variables, those related to temperature, specifically BIO6, BIO5, and BIO8, emerged as the most influential in shaping *U. europaeus* abundance (Fig. 5a). Notably, BIO8 also showed the highest Shapley values (Fig. 5b), although the contribution of each abiotic variable varied across different abundance classes (Fig. 5c). In Tenerife, the model prediction indicates some new potential areas of establishment of the species on the windward side of the island.

The MESS index consistently identified areas of extrapolation across various climatic scenarios, predominantly occurring in the driest islands of the archipelago, such as Fuerteventura and Lanzarote, as well as in the drier regions of the other islands (Fig. S3.5). Regarding the predicted abundance class of *U. europaeus* across the Canary Islands, an East–West aridity gradient was observed, which remained consistent irrespective of the climatic scenario under consideration (Fig. 6a; Fig. S3.6–S3.7).
<figure><img src="image_7.png" /><figcaption>**Fig. 4** Co-occurrence matrix of the invasive species in Tenerife Island (n = 47). Each panel displays the co-occurrence matrix associated with a specific class of *U. europaeus* abundance. Class 1 (a), Class 2 (b), Class 3 (c), Class 4 (d), and Class 5 (e) represent negative associations between species pairs, blue squares represent positive associations between species pairs, and grey squares represent random associations between species pairs. Class 1 (1 to 10 specimens); Class 2 (10–49 specimens); Class 3 (50–99 specimens); Class 4 (100–199 specimens); and Class 5 (> 200 specimens). *Ageratina adenophora* (Asteraceae): Aga; *Agave americana* L. (Asparagaceae):</figcaption></figure>

Aa; *Arundo donax* L. (Poaceae): Ad; *Centranthus ruber* (L.) DC. (Caprifoliaceae): Cer; *Chasmanthe floribunda*: Chf; *Cortaderia* spp. (Poaceae): Csp; *Cytisus scoparius* (L.) Link (Fabaceae): Cs; *Daphne gnidium* L. (Thymelaeaceae): Dg; *Delairea odorata* Lem. (Asteraceae): Do; *Eucalyptus* ssp. (Myrtaceae): Esp; *Erigeron karvinskianus* DC. (Asteraceae): Ek; *Opuntia* sp.: Osp; *Oxalis pes-caprae* L. (Oxalidaceae): Opc; *Pennisetum setaceum* (Forssk.) Chiov. (also known as *Cenchrus setaceus* (Forssk.) Morrone): Ps; *Pteridium aquilinum*: Pa; *Rubus ulmifolius* Schott (Rosaceae): Ru; *Sporobolus* sp (Poaceae): Sp

The easternmost and driest islands, Fuerteventura and Lanzarote, were deemed unsuitable for the species. Conversely, areas predicted to be more suitable to the presence and abundance of *U. europaeus* were situated on the windward sides of the other islands, characterised by cooler and more humid conditions. The proportion of grid cells occupied by the species, indicating the ratio of cells with predicted abundance class above or equal to one to the total number of grid cells, shows a decreasing trend for El Hierro, La Gomera, and Gran Canaria islands towards warmer climatic scenarios compared to the

current climatic conditions (Fig. 6b). Conversely, the trend is less pronounced for Tenerife and La Palma islands: on Tenerife, the proportion of occupied cells is anticipated to decline under SSP126 and SSP370 compared to current climatic conditions, with a subsequent rise under SSP585. Conversely, on La Palma, the proportion of occupied cells is projected to increase slightly under SSP126 but decrease under SSP370 and SSP585 scenarios. Notably, La Palma consistently exhibits the highest predicted proportion of occupied grid cells across all climatic scenarios.
<figure><img src="image_8.png" /><figcaption>**Fig. 5** Results of the Random Forest model assessing the environmental factors influencing the abundance of *U. europaeus* on Tenerife Island: **a** Variable importance, **b** Global average Shapley value, **c** Shapley values broken down for the</figcaption></figure>

different abundance categories. Class1 (1 to 10 specimens); Class2 (10–49 specimens); Class3 (50–99 specimens); Class4 (100–199 specimens); and Class5 (> 200 specimens)

<figure><img src="image_9.png" /><figcaption>**Fig. 6** a Predicted abundance of *Ulex europaeus* in the Canary Islands under current climate conditions and the SSP585 scenario. Currently, the species is only present on Tenerife Island. Lanzarote and Fuerteventura were not displayed because they</figcaption></figure>

were unsuitable for the four climatic scenarios investigated; all the scenarios are available in Fig. SM3.6-3.7; **b** Proportion of occupied grid cells in each island across different climatic scenarios

<figure><img src="image_10.png" /></figure>
## Discussion

Previous surveys on other species such as *Acacia farnesiana* (L.) Willd. (Fabaceae)(also known as *Vachellia farnesiana* (L.) Wight & Arn.) (Naranjo-Cigala et al. 2016) and *Nicotiana glauca* Graham (Solanaceae) (Naranjo-Cigala et al. 2017) have provided valuable insights into their distribution and their impact on native communities in the Canary Islands. These studies, based on bibliographic references, herbarium information, fieldwork, and cartographic data, served as a foundation and support for designing the methodology of this study. The results of this study have updated the knowledge on the current distribution of *U. europaeus* on Tenerife Island (García-Gallo et al. 1989), confirming the presence of the species in the northeast part of the island and better estimating the extent of the two populations located in the northwest part of the island. These results are particularly relevant in light of establishing early detection strategies for this species in other places in Tenerife (and by extension the entire Canary Islands), within the early-warning control programs developed by local authorities (e.g. Red Canaria de Alerta Temprana de Especies Exóticas Invasoras, RedEXOS).

The two largest populations of *U. europaeus* in the northwest area of the island coincide with the locations reported for the first records of this species (Buch 1825). This could suggest a very ancient introduction of this species in the northwest of the island and could indicate different introduction events for the population located in the northeast, but molecular analyses are necessary to confirm this hypothesis, similar to that carried out by Hornoy et al. (2013).

### Natural and anthropic drivers of *U. europaeus* abundance in Tenerife

The RF model used to investigate how the different natural and anthropogenic factors contribute to the abundance of *U. europaeus* in Tenerife Island suggested the significant influence of human-related variables, specifically anthropogenic pressure and access to roads. This aligns with previous research emphasising the substantial impact of human activities on native communities and invasive species distributions (Jones et al. 2016; McKinney 2006; Bacaro et al. 2015; Da Re et al. 2020). Anthropogenic pressure,

including land development and urbanisation, has been shown to alter habitat suitability and facilitate the spread of invasive species (Ricotta et al. 2019; Simberloff 2009; Tordoni et al. 2021). Similarly, road networks serve as corridors for invasive species dispersal, facilitating their colonisation of new areas (Arévalo et al. 2005; 2010; McKinney 2008; Bacaro et al. 2015).

### IAS co-occurrence patterns of *U. europaeus* depend on its abundance

The co-occurrence analysis showed that co-occurrence patterns between *U. europaeus* and other invasive species strongly depend on their level of abundance. We found significant positive associations, especially for lower levels of abundance which become predominantly positive for higher abundance class (Table S3.2). Interestingly, when all classes were pooled together we did not detect any significant association with the other IAS in Tenerife. This apparent discrepancy might be explained by extreme heterogeneity in the observations. Indeed, individual classes may be diluted due to the broader range of contexts and interactions included in the analysis or by the fact that *U. europaeus* may have strong associations with certain species due to specific environmental conditions or ecological interactions that are unique to those classes. When pooling classes, the specific conditions that favour these associations might be averaged out, leading to a lack of significant association across the entire dataset.

Notably, we observed an increase in positive associations with the abundance of *U. europaeus*, and this pattern is related to the average number of IAS in the cell (Fig. S3.3). This is in agreement with the so-called “invasion meltdown” hypothesis (Simberloff and Von Holle 1999; Daly et al. 2023), stating that already invaded areas may facilitate the proliferation of other IAS through change in the biotic and abiotic components in the community (Uboni et al. 2019; Calizza et al. 2021). For instance, it is known that *Ageratina adenophora* (Aga) invasion may affect soil nutrient dynamics, particularly phosphorus, potentially altering ecosystem functions and structure (Wu et al. 2020). Furthermore, this pattern suggests potential ecological similarities or shared environmental preferences among IAS species in Tenerife Island, which may contribute to their co-occurrence
and proliferation within invaded ecosystems. Other studies have already shown that invasive species often exhibit overlapping habitat preferences and ecological traits, facilitating their coexistence and expansion (Catford et al. 2011; Simberloff et al. 2013). Given their frequent association with human-induced disturbances, such as abandoned fields, road margins, and areas subjected to soil removal or intensive trampling, these invasive species exhibit a propensity to thrive in anthropogenically altered environments (McKinney 2006; Pyšek et al. 2012; Bacaro et al. 2015).

*U. europaeus* thrives in cooler environments in the Canary Islands

Under the current climatic scenario, the outputs of the habitat suitability model indicate that the easternmost and driest islands, Fuerteventura and Lanzarote, are unsuitable for the species. This aligns with expectations, as this species typically thrives and is more abundant in cool and humid environments (Atlan and Udo 2019; Christina et al. 2020). On the other islands, the areas predicted to be more suitable for *U. europaeus* presence and abundance are predominantly located on the windward sides, which are known for their relatively cooler and more humid conditions (Chazarra et al. 2011). Notably, this spatial pattern remained consistent across different climatic scenarios, suggesting that the observed distribution pattern of *U. europaeus* is robust and not significantly influenced by future climate projections. However, the total proportion of cells occupied by the species does reduce under future and warmer scenarios and can be related to the decrease of germination and establishment capacity of its seeds, thereby restricting their dispersal process and hindering colonisation or persistence in new areas (Udo et al. 2017; Atlan and Udo 2019). These findings are in agreement with the results of other studies employing SDM approaches over larger spatial extents (Hernández-Lambraño et al. 2017; Christina et al. 2020; Roberts and Florentine 2021; Ángel-Vallejo et al. 2024). In a similar study, Da Re et al. (2020) examined the habitat suitability dynamics of *Pennisetum setaceum*, another invasive plant species in Tenerife, yielding similar findings. Despite utilising less sophisticated climate change scenarios, their results also indicated increased suitability under climate change for more humid and cooler areas of the island.

It is worth noting that the highest predicted abundance values were observed in Tenerife, which served as the training island for our model, whilst for the other islands the model predominantly predicts the average values of the observed abundance distribution. This discrepancy may reflect the higher certainty associated with predictions in Tenerife due to its status as the training dataset, while the predictions for other islands are more generalised. Furthermore, the apparent absence of significant invasion on the other islands, despite predicted suitability, raises questions about the factors influencing the dispersion of the species.

While SDMs have been effectively used to assess the potential spread of various invasive plant species—such as *Pennisetum setaceum* on Tenerife (Da Re et al. 2020), *Cytisus scoparius* in New Zealand, and *Hakea sericea* in South Africa (Wiser and Leduc 2011; Midgley et al. 2016)—it is important to recognize that these models rely on several key assumptions that can limit their accuracy and define their usage boundaries (Guisan et al. 2017). One of the main assumptions is that the species is in (or near) equilibrium with its environment, meaning it has already colonized all suitable locations while being absent from unsuitable ones (Hattab et al. 2017). This assumption was also made in our study. Additionally, we acknowledge that using only three climate scenarios and five models (GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-LR, MRI-ESM2-0, UKESM1-0-LL) may have limited our ability to fully capture the range of possible future conditions and their impacts on the species. However, our decision to use CanaryClim was driven by data availability; it is the only dataset that offers high spatial resolution climate change scenarios specifically for the Canary Archipelago, making it the most suitable option for our research.

## Management practices

Effective management approaches should prioritise mitigating anthropogenic impacts, such as reducing habitat fragmentation and implementing measures to minimise the spread of invasive species via road networks (Simberloff and Von Holle 1999). Integrating landscape-scale planning and habitat restoration efforts can further enhance the resilience of native ecosystems to invasive species by restoring and maintaining ecological connectivity (Hobbs
et al. 2009). Currently, in the Canary Islands, there needs to be more specific programs aimed at rehabilitating abandoned agricultural areas, primarily due to challenges in identifying landowners and addressing variations in soil categories and management practices. Although some areas have witnessed successful restoration efforts, such as the recovery of approximately 20,000 hectares of *native forest* stands on the island since 1996 (Pardo et al. 2012), it is noteworthy that not all restored areas feature native species, with exotic species like *Eucalyptus camaldulensis*, *E. globulus* or *Pinus radiata* being employed, and in certain instances, samples from continental Spain were transported to the Canary Islands for restoration purposes (Marrero 2016).

Furthermore, *U. europaeus* is a fire-prone species that significantly modifies the frequency and intensity of fire across the landscape by increasing the amount of necromass and biomass, primarily dead branches and spines, thereby intensifying and promoting fire (Altamirano et al. 2016). Fires also facilitate the germination and dispersion of *U. europaeus*, and while high-intensity fires can harm the native plant community, *U. europaeus* is highly adapted to such conditions (Roberts and Florentine 2021). Cleaning areas after a fire has become another important factor favouring the dispersion and germination of *U. europaeus*. Therefore, post-fire management efforts should focus on restoration and mechanical eradication of the species to prevent its dominance in the area, as observed in previous incidents. Recent management practice field experiments, combining chemical treatments, mechanical removal, and the plantation of native species, have shown improved results in restoring native plant communities (González-Montelongo et al., 2024).

Additionally, considering the recognised presence of the species along secondary roads and trails, the introduction of biosecurity hygiene practices, such as boot brushing, could be a low-impact management strategy that people can adopt to help prevent the introduction and dispersal of IAS, as already adopted in some areas of the United States of America and Australia (Gill et al. 2020; Dolman and Marion 2022; HDLNR 2022).

The results of our research contribute to a deeper understanding of the ecological dynamics of *U. europaeus* in isolated oceanic islands, offering valuable information on its potential dispersion patterns in

response to climate change. These findings not only enhance our knowledge of the species but also provide essential support for conservation efforts by helping to formulate informed strategies tailored to the unique ecological challenges posed by *U. europaeus* in the Canary Islands.

**Acknowledgements** We thank the “Fundación CajaCanarias y Fundación La Caixa” (2017REC16), the “Exmo. Cabildo Insular de Tenerife” and GESPLAN S.L. for funding and supporting this study. Special thanks are extended to the geographers Marco A. Márquez García and Mario H. Gil Sánchez for their dedication and effort in conducting fieldwork for the chorological mapping of the species.

**Author contributions** Agustín Naranjo-Cigala, Miguel Antonio Padrón-Mederos, Maya González, Cristina González-Montelongo and José Ramón Arevalo Sierra conceived the ideas and designed the sampling strategy; Agustín Naranjo-Cigala and Miguel Antonio Padrón-Mederos collected the data; Daniele Da Re and Enrico Tordoni analysed the data; Daniele Da Re led the writing of the manuscript. All authors contributed critically to the drafts and gave final approval for publication.

**Funding** Open access funding provided by Università degli Studi di Trento within the CRUI-CARE Agreement.

**Data availability** The data and the R scripts used to perform the analysis are available on request to the corresponding author.

**Open Access** This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

## References

* Altamirano A, Cely JP, Etter A, Miranda A, Fuentes-Ramírez A, Acevedo P et al (2016) The invasive species *Ulex europaeus* (Fabaceae) shows high dynamism in a fragmented landscape of south-central Chile. Environ Monit Assess 188(8):495–510

* Álvarez Escobar A (2011) Contribución al estudio etnobotánico de la isla de Tenerife. Tesis doctoral (ined.). Facultad de
Biología, Dpto. de Biología Vegetal (Botánica), Universidad de La Laguna

Ángel-Vallejo MC, Aguirre-Acosta N, Rodríguez-Rey GT, García-Marín EJ, Álvarez-Mejía LM, Feuillet-Hurtado C (2024) Distribution models in invasive plants with climatic niche expansion: a case study of *Ulex europaeus* L. in Colombian Andes. *Biol Invasions*. https://doi.org/10.1007/s10530-024-03285-7

Arévalo JR, Delgado JD, Otto R, Naranjo-Cigala A, Salas M, Fernández-Palacios JM (2005) Distribution of alien vs. native plant species in roadside communities along an altitudinal gradient in Tenerife and Gran Canaria (Canary Islands). *Perspect Plant Ecol Evolut Syst* 7(3):185-202

Arévalo JR, Afonso L, Naranjo-Cigala A et al (2010) Invasion of the Gran Canaria ravines ecosystems (Canary Islands) by the exotic species *Acacia farnesiana*. *J Plant Ecol* 206:185-193

Arévalo JR, Tejedor M, Jiménez C, Reyes-Betancort JA, Díaz FJ (2016) Plant species composition and richness in abandoned agricultural terraces vs. natural soils on Lanzarote (Canary Islands). *J Arid Environ* 124:165-171

Arévalo JR, Fernández-Lugo S, Reyes-Betancort JA, Tejedor M, Jiménez C, Díaz FJ (2017) Relationships between soil parameters and vegetation in abandoned terrace fields vs. non-terraced fields in arid lands (Lanzarote, Spain): an opportunity for restoration. *Acta Oecologica* 85:77-84

Atkinson IAE, Cameron EW (1993) Human influence on the terrestrial biota and biotic communities of New Zealand. *Trends Ecol Evol* 8:447-451

Atlan A, Limbada F (2019) World distribution of gorse *Ulex europaeus* in introduced areas. *Geonetwork*, OSURIS.

Atlan A, Udo N (2019) The invasive niche, a multidisciplinary concept illustrated by Gorse (*Ulex europaeus*). *Diversity* 11(9):162

Bacaro G, Maccherini S, Chiarucci A, Jentsch A, Rocchini D, Torri D et al (2015) Distributional patterns of endemic, native and alien species along a roadside elevation gradient in Tenerife, Canary Islands. *Commun Ecol* 16:223-234

Bateman JB, Vitousek PM (2018) Soil fertility response to *Ulex europaeus* invasion and restoration efforts. *Biol Invasions* 20(10):2777-2791

Bellard C, Cassey P, Blackburn TM (2016) Alien species as a driver of recent extinctions. *Biol Let* 12(2):20150623

Benning TL, LaPointe D, Atkinson CT, Vitousek PM (2002) Interactions of climate change with biological invasions and land use in the Hawaiian Islands: modeling the fate of endemic birds using a geographic information system. *Proc Natl Acad Sci* 99(22):14246-14249

Brandt AJ, Bellingham PJ, Duncan RP, Etherington TR, Frideley JD, Howell CJ et al (2021) Naturalised plants transform the composition and function of the New Zealand flora. *Biol Invas* 23(2):351-366

Breiman L (2001) Random forests. *Mach Learn* 45(1):5-32

Broadfield N, McHenry MT (2019) A world of gorse: persistence of *Ulex europaeus* in managed landscapes. *Plants* 8(11):523. https://doi.org/10.3390/plants8110523

von Buch L (1825) Physikalische Beschreibung der Kanarischen Inseln. Berlín, Hofdruckerei von Königlichen Akademie, 2 vols. xiv+388+381 pp. [Bibliotheca Albertina,

Universität Leipzig] [reproducido en: Ewald et al. (1877), pp 229-646].

Calizza E, Rossi L, Careddu G, Sporta Caputi S, Costantini ML (2021) A novel approach to quantifying trophic interaction strengths and impact of invasive species in food webs. *Biol Invasions* 23(7):2093-2107

Gobierno de Canarias (2023) Estadística Anual de Superficies y Producciones de Cultivos / Series anuales. Municipios, islas y provincias de Canarias. 1999-2022. Instituto Canario de Estadística (https://www3.gobie.rnodecanarias.org/istac/statistical-visualizer/visualizer/collection.html?resourceType=collection&agencyId=ISTAC&resourceId=E01135A_000001) [consultada el 21/03/2024]

Gobierno de Canarias (2024) Banco de Datos de Biodiversidad de Canarias (https://www.biodiversidadcanarias.es/biota/) [consultada el 21/03/2024]

Caro T, Rowe Z, Berger J, Wholey P, Dobson A (2022) An inconvenient misconception: climate change is not the principal driver of biodiversity loss. *Conserv Lett* 15(3):e12868

Catford JA, Vesk PA, White MD, Wintle BA (2011) Hot-spots of plant invasion predicted by propagule pressure and ecosystem characteristics. *Divers Distrib* 17(6):1099-1110

Chazarra A, Mestre A, Cabrinha V, Cunha S, Pimpao A, Marques J, Carvalho F, Mendes MT, Neto J, Mendes L, Nunes LF (2011) Atlas Climático dos arquipélagos das Canárias, da Madeira e dos Açores. *Agencia Estatal de Meteorología-Instituto de Meteorología de Portugal, Madrid*

Christina M, Limbada F, Atlan A (2020) Climatic niche shift of an invasive shrub (*Ulex europaeus*): a global scale comparison in native and introduced regions. *J Plant Ecol* 13(1):42-50

Christina M, Gire C, Bakker MR, Leckie A, Xue J, Clinton PW, et al (2023) Native and invasive seedling drought-resistance under elevated temperature in common gorse populations. *J Plant Ecol* 16(3):rtac097

Clements DR, Peterson DJ, Prasad R (2001) The biology of Canadian weeds 112. *Ulex europaeus* L. Can J Plant Sci 81(2):325-337

Da Re D, Tordoni E, Pérez ZN, Fernández-Palacios JM, Arévalo JR, Otto R et al (2019) A spatially-explicit model of alien plant richness in Tenerife (Canary Islands). *Ecol Comple* 38:75-82

Da Re D, Tordoni E, De Pascalis F, Negrín-Pérez Z, Fernández-Palacios JM, Arévalo JR et al (2020) Invasive fountain grass (*Pennisetum setaceum* (Forssk.) Chiov.) increases its potential area of distribution in Tenerife island under future climatic scenarios. *Plant Ecol* 221:867-882

Da Re D, Tordoni E, Lenoir J, Lembrechts JJ, Vanwambeke SO, Rocchini D, Bazzichetto M (2023) USE it: Uniformly sampling pseudo-absences within the environmental space for applications in habitat suitability models. *Methods Ecol Evol* 14:2873-2887. https://doi.org/10.1111/2041-210X.14209

Daly EZ, Chabrerie O, Massol F, Facon B, Hess MC, Tasiemski A et al (2023) A synthesis of biological invasion hypotheses associated with the introduction-naturalisation-invasion continuum. *Oikos* 202(5):e09645

<figure><img src="image_11.png" /></figure>
Dolman MR, Marion JL (2022) Invasive plant hitchhikers: appalachian Trail thru-hiker knowledge and attitudes of invasive plants and leave No trace practices. J Outdoor Recreat Tour 40:100581

Donlan CJ, Wilcox C (2008) Diversity, invasive species and extinctions in insular ecosystems. J Appl Ecol 45:1114–1123

Elith J, Leathwick JR (2009) Species distribution models: eco-
logical explanation and prediction across space and time.
Annu Rev Ecol Evol Syst 40:677–697. https://doi.org/10.
1146/annurev.ecolsys.110308.120159

Elith J, Kearney M, Phillips S (2010) The art of modelling range-shifting species. Methods Ecol Evol 1(4):330–342

Elorza MS, Sánchez EDD, Vesperinas ES, Nacionales OAP (eds) (2004) Atlas de las plantas alóctonas invasoras en España. Organismo Autónomo Parques Nacionales.

Essl F, Lenzner B, Bacher S et al (2020) Drivers of future alien species impacts: an expert-based assessment. Glob Change Biol 26:4880–4893. https://doi.org/10.1111/gcb. 15199

Evans JS, Murphy MA, Holden ZA, Cushman SA (2010) Mod-
eling species distribution and change using random for-
est. In Predictive species and habitat modeling in land-
scape ecology: concepts and applications. Springer, New
York, pp 139–159

Galappaththi HSD, de Silva WPP, Clavijo Mccormick A (2023) A mini-review on the impact of common gorse in its introduced ranges. Trop Ecol 64(1):1–25

García-Gallo A, Wildprett W, del Arco MJ, Pérez de Paz JL (1989) Sobre la presencia de *Ulex europaeus* L. en la isla de Tenerife. Boletim Da Sociedade Broteriana 62:221–225

García-Gallo A, Wildpret W, Martín V (2008) Especies veg-
etales consideradas invasoras de hábitats, en la Historia
Natural de Canarias. Lazaroa (España) 29:49–67

Gill N, McKiernan S, Lewis A, Cherry H, Annunciato D (2020) Biosecurity hygiene in the Australian high country: footwear cleaning practices, motivations, and barriers among visitors to Kosciuszko National park. Aust J Environ Manage 27(4):378–395

González-Montelongo C, Padrón-Mederos MA, Negrín-Pérez Z, González M, Arévalo JR (2024) Management strategies for Ulex europaeus L. Control in a native plant community in Tenerife, Canary Islands: Impact of eradication in a native plant community (Tenerife, Canary Islands). Agriculture 14(10):1683

Griffith DM, Veech JA, Marsh CJ (2016) Cooccur: probabil-
istic species co-occurrence analysis in R. J Stat Softw
69(2):1–17. https://doi.org/10.18637/jss.v069.c02

Guisan A, Thuiller W, Zimmermann NE (2017) Projecting models in space and time. In Habitat suitability and distribution models: with applications in R. Cambridge University Press, pp 303–348

Guisan A, Thuiller W (2005) Predicting species distribution: offering more than simple habitat models. Ecol Lett 8(9):993–1009. https://doi.org/10.1111/j.1461-0248. 2005.00792.x

Hattab T, Garzón-López CX, Ewald M, Skowronek S, Aerts
R, Horen H, Brasseur B, Gallet-Moron E, Spicher F,
Decocq G, Feilhauer H, Honnay O, Kempeneers P,
Schmidtlein S, Somers B, van de Kerchove R, Rocchini

D, Lenoir J (2017) A unified framework to model the potential and realized distributions of invasive species within the invaded range. Divers Distrib 23(7):806–819

Hawaiʻi Department of Land and Natural Resources (HDLNR, 2022) New boot brush stations deployed in the fight against Rapid ‘Ōhi’a Death. Forestry & Wildlife, News Releases, Slider, Trail. https://dlnr.hawaii.gov/blog/2022/ 07/21/nr22-103/

Hernández-Lambraño RE, González-Moreno P, Sánchez-Agudo JÁ (2017) Towards the top: niche expansion of Taraxacum officinale and *Ulex europaeus* in mountain regions of South America. Austral Ecol 42(5):577–589

Hobbs RJ, Higgs E, Harris JA (2009) Novel ecosystems: impli-
cations for conservation and restoration. Trends Ecol
Evol 24(11):599–605

Hornoy B, Atlan A, Roussel V, Buckley YM. Tarayre M (2013) Two colonisation stages generate two different patterns of genetic diversity within native and invasive ranges of *Ulex europaeus*. Heredity 111(5):355–363

Hulme PE (2009) Trade, transport and trouble: managing inva-
sive species pathways in an era of globalization. J Appl
Ecol 46:10–18

Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) (2023) Summary for Policymakers of the Thematic Assessment Report on Invasive Alien Species and their Control of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. Roy HE, Pauchard A, Stoett P, Renard Truong T, Bacher S, Galil BS, Hulme PE, Ikeda T, Sankaran KV, McGeoch MA, Meyerson LA, Nuñez MA, Ordonez A, Rahlao SJ, Schwindt E, Seebens H, Sheppard AW, Vandvik V (eds) IPBES secretariat, Bonn, Germany. https://doi.org/10.5281/zenodo.7430692

Roy HE, Pauchard A, Stoett P, Renard Truong T, Bacher S, Galil BS, Hulme PE, Ikeda T, Sankaran KV, McGeoch MA, Meyerson LA, Nuñez MA, Ordonez A, Rahlao SJ, Schwindt E, Seebens H, Sheppard AW Intergovernmen- tal Science-Policy Platform on Biodiversity and Eco- system Services (IPBES) (2023). Summary for Policy- makers of the Thematic Assessment Report on Invasive Alien Species and their Control of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. Vandvik V (eds.) IPBES secretariat, Bonn, Germany. https://doi.org/10.5281/zenodo.7430692

Iseli E, Chisholm C, Lenoir J, Haider S, Seipel T, Barros A, et al (2023) Rapid upwards spread of non-native plants in mountains across continents. Nat Ecol Evol, pp 1–9

Jones HP, Holmes ND, Butchart SH, Tershy BR, Kappes PJ, Corkery I et al (2016) Invasive mammal eradication on islands results in substantial conservation gains. Proc Natl Acad Sci 113(15):4033–4038

Karger DN, Conrad O, Böhner J, Kawohl T, Kreft H, Soria-Auza RW et al (2017) Climatologies at high resolution for the earth's land surface areas. Sci Data 4(1):1–20

Kariyawasam CS, Ratnayake SS (2019) Reproductive biology of gorse, *Ulex europaeus* (Fabaceae) in the Mount Lofty Ranges of South Australia and Sri Lanka. Int J Plant Reproduct Biol 11(2):145–152

Kier G, Kreft H, Lee TM, Jetz W, Ibisch PL, Nowicki C, Mutke
J, Barthlott W (2009) A global assessment of endemism
and species richness across island and mainland regions.
Proc Natl Acad Sci 106(23):9322-9327

Kuebbing SE, Nuñez MA (2015) Negative, neutral, and posi-
tive interactions among nonnative plants: patterns, pro-
cesses, and management implications. Glob Change Biol
21:926-934. https://doi.org/10.1111/gcb.12711

Kuebbing SE, Nuñez MA, Simberloff D (2013) Current mis-
match between research and conservation efforts: the
need to study co-occurring invasive plant species. Biol
Cons 160:121-129. https://doi.org/10.1016/j.biocon.
2013.01.009

Kueffer C, Daehler C, Torres-Santana CW, Lavergne C, Meyer J, Otto R, Silva L (2010) A global comparison of plant invasions on oceanic islands. Perspect Plant Ecol Evol Syst 12:145-161

Kuhn M (2008) Building predictive models in R using the caret package. J Stat Softw 28(5):1-26. https://doi.org/10.18637/jss.v028.i05

Kursa MB, Rudnicki WR (2010) Feature selection with the Boruta package. J Stat Softw 36:1-13

León Cordero R, Torchelsen FP, Overbeck GE, Anand M (2016) Invasive gorse (Ulex europaeus, Fabaceae) changes plant community structure in subtropical forest-grassland mosaics of southern Brazil. Biol Invasions 18:1629-1643

Levine JM, Adler PB, Yelenik SG (2004) A meta-analysis of biotic resistance to exotic plant invasions. Ecol Lett 7(10):975-989

Liaw A, Wiener M (2002) Classification and regression by ran-
dom. Forest R News 2(3):18-22

Lortie CJ, Filazzola A, Brown C, Lucero J, Zuliani M, Ghaz-
ian N et al (2021) Facilitation promotes plant invasions
and indirect negative interactions. Oikos 130:1056-1061.
https://doi.org/10.1111/oik.08443

Lundberg SM, Lee SI (2017) A unified approach to interpret-
ing model predictions. Adv Neural Inf Process Syst 30

Marrero Á (2016) Eucaliptos en Gran Canaria, identificación y corología. Hacia Una Reseña Histórica Botánica Macaronésica 29:91-137

Martín JL, Marrero MC, Zurita N, Arechavaleta M, Izquierdo I (2005) Biodiversidad en gráficas. Especies silvestres de las Islas Canarias. Consejería de Medio Ambiente y Ordenación Territorial, Gobierno de Canarias

McKinney ML (2006) Urbanization as a major cause of biotic homogenization. Biol Cons 127(3):247-260

McKinney ML (2008) Effects of urbanization on species richness: a review of plants and animals. Urban Ecosyst 11(2):161-176

Midgley GF, Thuiller W, Hughes G (2016) The role of species distribution models in assessing the risk of plant invasions. J Appl Ecol 53(4):976-984

Morente-López J, Arjona Y, Salas-Pascual M, Reyes-Betancort JA, del Arco-Aguilar MJ, Emerson BC et al (2023) Bio-geographic origins and drivers of alien plant invasions in the Canary Islands. J Biogeograph 50(3):576-590

Moser D, Lenzner B, Weigelt P, Dawson W, Kreft H, Pergl J et al (2018) Remoteness promotes biological invasions on islands worldwide. Proc Natl Acad Sci 115(37):9270-9275

Mosher ES, Silander JA, Latimer AM (2009) The role of land-
use history in major invasions by woody plant species in

the northeastern North American landscape. Biol Invasions 11:2317-2328

Muthulingam P, Marambe B (2022) The invasive weed Gorse (Ulex europaeus L.) in Sri Lanka: Implications of Naturalization over a Century. Weeds-J Asian-Pacific Weed Sci Soc 4(1):21-35

Naranjo-Cigala A, Salas M, Agudo L et al (2009) Studies on the distribution and characteristics of an allochthonous population of *Acacia farnesiana*. Open Forest Sci J 2:91-97

Naranjo-Cigala A, Salas M, Arévalo JR, Márquez M, Gil MH (2016) Actualización de la información corológica de *Acacia farnesiana* en Canarias y elaboración de propuestas para su control y/o erradicación. Informe técnico: Memoria Final y Cartografía. Gobierno de Canarias-Unión Europea

Naranjo-Cigala A, Salas M, Arévalo JR, Márquez M, González-García A, Gil MH (2017) Evaluación del grado de afección del hábitat 8320 campos de lava y excavaciones naturales por la especie *Nicotiana glauca* en las islas de Lanzarote y Fuerteventura y elaboración de una propuesta para la conservación de este hábitat. Informe técnico: Memoria Final y Cartografía. Gobierno de Canarias-Unión Europea

Panareda JM (2000) Cartografía y representación fitogeográfica. Meaza. G. et al. Metodología y Práctica de la Biogeografía. Ediciones del Serbal, Barcelona, pp 274-289

Pardo F, Velasco A, Gil L (2012) La transformación histórica del paisaje forestal en Canarias. Ministerio de Agricultura, Alimentación y Medio Ambiente, Madrid

Patiño J, Collart F, Vanderpoorten A, Martin-Esquivel JL, Naranjo-Cigala A, Mirolo S, Karger DN (2023) Spatial resolution impacts projected plant responses to climate change on topographically complex islands. Divers Distrib 29(10):1245-1262

Pauchard A, Kueffer C, Dietz H, Daehler CC, Alexander J, Edwards PJ et al (2009) Ain't no mountain high enough: plant invasions reaching new elevations. Front Ecol Environ 7(9):479-486

Pichler M, Hartig F (2023) Machine learning and deep learning—a review for ecologists. Methods Ecol Evol 14(4):994–1016

Plants of the World Online (POWO) (2023) Facilitated by the Royal Botanic Gardens, Kew. Published on the Inter-net; http://www.plantsoftheworldonline.org/. Retrieved 14 March 2024

Plants of the World Online (POWO) (2023) Facilitated by the Royal Botanic Gardens, Kew. Published on the Inter-net; http://www.plantsoftheworldonline.org/. Retrieved 14 March 2024

Pyšek, Petr, David M. Richardson (2010) Invasive species, environmental change and management, and health. Annual Rev Environ Res 35(1):25-55

Pyšek P, Jarošík V, Hulme PE, Pergl J, Hejda M, Schaffner U, Vilà M (2012) A global assessment of invasive plant impacts on resident species, communities and ecosystems: the interaction of impact measures, invading species' traits and environment. Glob Change Biol 18(5):1725-1737

<figure><img src="image_12.png" /></figure>
Ricotta C, Celesti-Grapow L, Pyšek P, Rapson GL (2019) The biogeography of naturalized alien plants in Italy. Perspect Plant Ecol Evol Syst 38:77–85

Roberts J, Florentine S (2021) Biology, distribution and control of the invasive species *Ulex europaeus* (Gorse): a global synthesis of current and future management challenges and research gaps. Weed Res 61(4):272–281

Rodríguez-Alarcón S, González-M R, Carmona CP, Tordoni E (2024) Trait-growth relationships in Colombian tropical dry forests: Incorporating intraspecific variation and trait interactions. J Veg Sci 35(1):e13233

Romero D, Sosa B, Brazeiro A, Achkar M, Guerrero JC (2021) Factors involved in the biogeography of the honey locust tree (*Gleditsia triacanthos*) invasion at regional scale: an integrative approach. Plant Ecol 222(6):705–722

Ryo M, Angelov B, Mammola S, Kass JM, Benito BM, Hartig F (2021) Explainable artificial intelligence enhances the ecological interpretability of black-box species distribution models. Ecography 44(2):199–205

Sanz-Elorza M, Dana ED, Sobrino, E (2004) Aproximación al listado de plantas vasculares alóctonas invasoras reales y potenciales en las islas Canarias. Mediterránean Botany, 26:55

Sax DF, Stachowicz JJ, Brown JH, Bruno JF, Dawson MN, Gaines SD et al (2005) Ecological and evolutionary insights from species invasions. Trends Ecol Evol 20(5):262–269

Schoener TW (1989) Ecological niches: a unified theory of biogeography. Princeton University Press

Shea K, Chesson P (2002) Community ecology theory as a framework for biological invasions. Trends Ecol Evol 17(4):170–176

Silva L, Smith CW (2004) A characterization of the non-indigenous flora of the Azores Archipelago. Biol Invasions 6:193–204

Simberloff D (2009) The role of propagule pressure in biological invasions. Annu Rev Ecol Evol Syst 40:81–102

Simberloff D, Von Holle B (1999) Positive interactions of non-indigenous species: invasional meltdown? Biol Invasions 1(1):21–32

Simberloff D, Martin JL, Genovesi P, Maris V, Wardle DA, Aronson J, Vilà M (2013) Impacts of biological invasions: what’s what and the way forward. Trends Ecol Evol 28(1):58–66

Stohlgren TJ, Barnett D, Flather C, Fuller P, Peterjohn B, Kartesz J, Master LL (2006) Species richness and patterns of invasion in plants, birds, and fishes in the United States. Biol Invasions 8:427–447

Tordoni E, Petruzzellis F, Nardini A, Savi T, Bacaro G (2019) Make it simpler: Alien species decrease functional

diversity of coastal plant communities. J Veg Sci 30(3):498–509

Tordoni E, Bacaro G, Weigelt P, Cameletti M, Janssen JA, Acosta AT et al (2021) Disentangling native and alien plant diversity in coastal sand dune ecosystems worldwide. J Veg Sci 32(1):12861

Uboni C, Tordoni E, Brandmayr P, Battistella S, Bragato G, Castello M et al (2019) Exploring cross-taxon congruence between carabid beetles (Coleoptera: Carabidae) and vascular plants in sites invaded by Ailanthus altissima versus non-invaded sites: The explicative power of biotic and abiotic factors. Ecol Ind 103:145–155

Udo N, Tarayre M, Atlan A (2017) Evolution of germination strategy in the invasive species *Ulex europaeus*. J Plant Ecol 10(2):375–385

Udo N, Darrot C, Atlan A (2018) From useful to invasive, the status of gorse on Reunion Island. J Environ Manage 229(1):166–173

Veech JA (2013) A probabilistic model for analysing species co-occurrence. Glob Ecol Biogeogr. https://doi.org/10.1111/j.1466-8238.2012.00789.x

Vujanović D, Losapio G, Milić S, Milić D (2022) The impact of multiple species invasion on soil and plant communities increases with invasive species co-occurrence. Front Plant Sci 13:875824

Westphal MI, Browne M, MacKinnon K, Noble I (2008) The link between international trade and the global distribution of invasive alien species. Biol invasions 10:391–398

Whittaker RJ, Fernández-Palacios JM (2007) Island biogeography: ecology, evolution, and conservation. Oxford University Press

Wiser SK, Leduc AS (2011) Modelling the potential distribution of *Cytisus scoparius* in New Zealand. J Biogeogr 38(8):1450–1461

Wu X, Duan C, Fu D, Peng P, Zhao L, Jones DL (2020) Effects of Ageratina adenophora invasion on the understory community and soil phosphorus characteristics of different forest types in southwest China. Forests 11(8):806

Zenni RD, da Cunha WL, Musso C, de Souza JV, Nardoto GB, Miranda HS (2020) Synergistic impacts of co-occurring invasive grasses cause persistent effects in the soil-plant system after selective removal. Funct Ecol 34(5):1102–1112. https://doi.org/10.1111/1365-2435.13524

**Publisher's Note** Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.