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Article

What Insight Does the Alien Plant Species Richness in Greece Offer for the Different Invasion Biology Hypotheses?

by
Athanasios Kallimanis
1,*,
Ioannis P. Kokkoris
2,
Ioannis Bazos
3,
Thomas Raus
4,
Arne Strid
5 and
Panayotis Dimopoulos
2
1
Department of Ecology, School of Biology, Aristotle University, 54124 Thessaloniki, Greece
2
Division of Plant Biology, Department of Biology, University of Patras, 26504 Patras, Greece
3
Department of Ecology and Systematics, Faculty of Biology, National and Kapodistrian University of Athens, Panepistimiopolis, 15701 Athens, Greece
4
Botanischer Garten und Botanisches Museum Berlin, Freie Universität Berlin, Königin-Luise-Straße 6-8, 14191 Berlin, Germany
5
Bakkevej 6, DK-5853 Ørbæk, Denmark
*
Author to whom correspondence should be addressed.
Diversity 2023, 15(10), 1067; https://doi.org/10.3390/d15101067
Submission received: 13 August 2023 / Revised: 3 October 2023 / Accepted: 4 October 2023 / Published: 8 October 2023
(This article belongs to the Section Biodiversity Conservation)
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Abstract

:
Biological invasions are one of the main threats to biodiversity, but they also offer insights on different ecological processes, as highlighted by the hypotheses posited to explain the phenomenon. We explore the relative importance of different hypotheses using biotic (native diversity) and abiotic factors (climate and landscape configuration) as proxies driving the spatial pattern of alien plant biodiversity in Greece. The strongest predictor of alien species richness is native species richness. Landscape heterogeneity boosts this relationship, but native and alien species prefer different conditions. Landscape composition and configuration explain more of the variance of alien diversity than of native diversity, with native diversity increasing at more naturally vegetated areas and alien diversity at agricultural lands. Climate is associated more strongly with native diversity than with alien diversity, with native diversity increasing in colder regions and alien diversity in warmer regions. The transportation network was associated with higher alien species richness but not with native species richness, highlighting the importance of propagule/colonization pressure. These differences might indicate that aliens occupy part of the niche space that is not preferred by the natives and thus allow us to speculate on the role of limiting similarity as a driving force.

1. Introduction

Biological invasions are considered one of the main threats to biodiversity, with detrimental impacts on ecosystem functioning and services. It is estimated that biological invasions cost EUR 12 billion per year to the European Union (EU) Member States’ economies [1]. So, trying to understand the factors that influence the potential of an area to receive alien species and ultimately predict the patterns of alien species is of critical importance for nature conservation and ecosystem management.
Simultaneously, the spread of alien species in novel environments offers an opportunity to advance ecological knowledge by understanding the processes of range expansion and biotic interactions. Given the practical implications and the theoretical interest, a plethora of hypotheses have been put forward to explain the process [2]. Most of these hypotheses are not mutually exclusive and may act simultaneously and even synergistically. Enders et al. [3] recently grouped all these hypotheses into five clusters: propagule, resource availability, traits, biotic interactions, and Darwin’s clusters. While experiments could theoretically test hypotheses one at a time, in real ecosystems, it is more than likely that many of them co-occur and interact in shaping alien species distributions. One approach to assessing multiple hypotheses in invasion biology is by examining the association of alien species richness with various environmental factors reflecting different processes [4,5].
Propagule and/or colonization pressure hypotheses (among the most often cited) focus on the introduction events of either individuals of one species (propagule pressure) or of different species (colonization pressure) [6,7]. Since introduction events are rarely known in real time, we cannot measure them directly. Thus, most of the published evidence supporting these hypotheses in the real world does not quantify introduction events per se but relies on surrogate measures such as urban areas, transportation networks, and ports or airports [7,8,9].
The resource availability cluster of hypotheses refers to the characteristics of the areas that mediate the establishment of alien species and reflects mechanisms like increased resource availability, environmental heterogeneity, disturbance, and empty niches as potential mechanisms [3,4]. Resources and niches are well established but difficult to quantify concepts since they could potentially reflect an almost infinite number of factors. Thus, examinations of these hypotheses rely most often on proxies like the composition and diversity of the landscape as a potential path for decreasing interspecific competition and allowing the establishment and propagation of alien species [9,10,11].
Darwin’s cluster of hypotheses reflects the biotic features of the community [3]. This group includes some of the more mutually exclusive hypotheses. For example, Elton’s biotic resistance hypothesis assumes that the more exhaustively resources are utilized by the native community, the harder it will be for the alien species to establish, which usually means that in areas of high native diversity, aliens will perform poorly, while the biotic acceptance hypothesis assumes that areas supporting many native species could also support many alien species [12]. And perhaps counterintuitively, there are cases where one pattern appears at fine scales while another at coarse scales, a phenomenon known as the invasion paradox [13]. Similarly, contradictory hypotheses exist for how invasion success may benefit from increased or decreased phylogenetic and/or functional relatedness between alien and native species [14,15,16,17].
The Mediterranean is recognized as a hotspot of biodiversity globally [18], characterized by a high degree of endemism [19], but it is also highlighted as a region of many and impactful biological invasions [20]. These invasions pose threats to species, ecosystems, and ecosystem functioning, as well as to ecosystem services and the economy [21,22]. This trend is exacerbated since the number of unintentional introductions in the area continues to grow [23,24] and subsequently, so does the cost of invasive species management and the derived economic loss [25]. So, there is a pressing conservation need to comprehend the mechanisms of biological invasions in the Mediterranean biodiversity hotspots.
Greece is one of the most species-rich countries in Europe and the Mediterranean, with more than 7900 plant species and subspecies, including a considerable proportion (more than 1600 species and subspecies, approximately 20% of the total), being endemic to Greece [26,27,28]. Greece lies at the intersection of Europe, Asia, and Africa and has been receiving alien species for millennia, but the number of introductions has increased over the past century. Also, the origin of the alien species has become more distant. This poses a potential threat to the conservation of its native flora. Simultaneously, this provides an opportunity to investigate how biotic factors (like native species richness) and abiotic factors (like climate and landscape configuration) affect alien species richness and how these associations could be interpreted in the framework of the different hypotheses regarding biological invasions. Here, we aim to analyze the spatial patterns of alien plant species in Greece and their drivers to explore to what extent the observed associations are in accordance with the predictions of different hypotheses. Here, we aim to identify the most important predictors of alien species richness and how other environmental factors mediate this relationship. This analysis will take place not at the local scale of sampling plots but at the regional scale, including all the terrestrial territory of Greece where conservation policies are undertaken under the provisions of the National and the European Biodiversity Strategy, and simultaneously supporting the national efforts for the MAES (mapping and assessment of ecosystems and their services) implementation and natural capital accounting in Greece [29]. This analysis may highlight the different mechanisms shaping the expansion of alien plant species in Greece and thus inform on the options available for conservation policy.

2. Materials and Methods

2.1. Greek Plant Biodiversity Data

Based on the database on alien plants in Greece [30] and the corresponding online platform (https://www.alienplants.gr/ accessed on 8 September 2023), the Greek flora includes 457 alien plant species. Distribution data for alien and native species derived from the Flora Hellenica Database and maintained by one of us (AS), the most extensive and detailed database of plants occurring in Greece (more than 1.2 M occurrences of approximately 7450 native “species” and 457 alien “species” (established and non-established aliens). The term “species” includes both plant species and subspecies. Spatial and GIS analyses were undertaken using the 10 km × 10 km EEA (European Environment Agency) reference grid for Greece.

2.2. Environmental Factors as Drivers of Biodiversity

We used three climatic variables retrieved from the WorldClim climate database: mean annual temperature, temperature seasonality, and precipitation seasonality [31]. We used only three of the nineteen WorldClim bioclimatic variables due to the strong collinearity among the bioclimatic variables. For example, in Greece, the driest quarter of the year is also the hottest quarter of the year. We also analyzed landscape structure using both estimates of the area covered by the different land cover classes and of landscape diversity and fragmentation. We used four variables related to the area occupied by different land cover classes: agricultural land area, artificial surfaces, natural vegetation, and wetland areas, corresponding to the first hierarchical level of the Corine Land Cover classification scheme. Land cover diversity and fragmentation were estimated using the finest thematic resolution data of Corine land cover (the third hierarchical level of the CLC scheme includes 44 thematic classes). More specifically, the diverse Greek landscape is documented by the correspondence of the CLC classes in Greece to the Mediterranean region land cover attributes and unique vegetation characteristics. In more detail and based on the most updated ecosystem type map of Greece [32], Corine land cover classes in Greece correspond to vegetation types like Mediterranean deciduous and coniferous forests, temperate deciduous and mountainous forests, mixed forests, floodplain forests, sclerophyllous vegetation, moors and heathland, grasslands, peat bogs, rivers and lakes, inland freshwater and saline marshes, sparsely vegetated areas, beaches, dunes and sands, and bare rocks. Landscape diversity was quantified as the different land cover classes observed across each cell (of the 10 km × 10 km EEA reference grid), while fragmentation was quantified as the mean number of patches per land cover class. Landscape data were provided by the land cover dataset CLC1990. To quantify the impact of the transport network on diversity patterns, we summed the area occupied by Corine classes 122 (road and rail networks), 123 (port areas), and 124 (airports). We also examined whether using Corine land cover data from a different period (namely 2000) would influence the results, but we found only quantitative differences and so present only the results for the 1990 dataset.

2.3. Statistical Analysis

We applied Generalized Additive Mixed Models (GAMMs) with the “gamm” function of the “mgcv” R package, predicting the species richness of alien and native plant species as a function of the climatic and landscape predictors. We used negative binomial error distribution for both alien and native species richness. To account for spatial autocorrelation in the variance structure of our data, we used the GAMM approach of including the spatial autocorrelation in the covariance structure. All the predictors were modeled as smooth predictors with penalized thin plate regression splines (k = 5). The area occupied by artificial surfaces and the number of patches per class were log-transformed. Grid cells with less than 70% terrestrial land cover or without any records were excluded from the analysis; the remaining 30% of the area was typically marine or fell outside the borders of Greece.
To avoid issues of collinearity in the models with multiple independent variables, we a priori selected variables that were not strongly correlated. We tested, and there was no pairwise linear correlation among our independent variables that displayed a correlation coefficient greater than 0.7. We used the Bonferroni adjustment for multiple comparisons and consider a relationship significant if p < 0.05/11, i.e., p < 0.004.
Here, we did not test the different invasion biology hypotheses directly, but indirectly. More specifically, to see which of the different hypotheses better explains our data, we examined the association between alien species richness and the different environmental factors. The different invasion biology hypotheses make different predictions about which biotic and abiotic factors are important in shaping the distribution of alien species and how the different factors should associate with the spatial pattern of alien species. The propagule pressure hypothesis predicts that aliens will be more abundant close to the points of introduction and thus implies a positive association between alien species richness and points of introduction of alien species (like ports, airports, and transport networks). The biotic acceptance hypothesis predicts that areas that are suitable and thus rich in native species will also be suitable and rich in alien species (strong positive association), while the biotic resistance hypothesis predicts that areas rich in native species will explore the available resources more thoroughly and provide fewer opportunities for alien species to establish what should appear as a negative association between native and alien diversity patterns. The empty niche hypothesis emphasizes the differences between the niches occupied by native and alien species. Since it is impossible to quantify the niche of different species, we used the climatic preferences of the species as a proxy for niche differences and examined if native and alien species richness displayed different climatic associations as an indicator supporting the empty niche hypothesis. As a proxy for the resource availability cluster of hypotheses, we used landscape configuration and examined if environmental heterogeneity (using landscape diversity as a proxy) affects alien species richness.
And because all these mechanisms do not operate in isolation, we also examined their relative contribution to shaping alien biodiversity patterns by building a combined model including all predictors and then removing those predictors that did not increase the overall deviance explained by the model.

3. Results

3.1. Alien Species Hotspots

The areas of highest alien plant species richness (38 to 77 alien taxa per 10 km × 10 km grid cell) across the Greek territory are found in western Greece, Peloponnisos, the urban and peri-urban area (Corine land cover classes: 111—continuous urban fabric; 112—discontinuous urban fabric; 121—industrial or commercial units; 122—road and rail networks and associated land; 123—port areas; 124—airports; 131—mineral extraction sites; 132—dump sites; 133—construction sites; 141—green urban areas; and 142—sport and leisure facilities) of large cities of mainland Greece (e.g., Athens, Thessaloniki, and Patras), the East Aegean islands, and Crete (Figure 1a).

3.2. Species Richness Predictors’ Analyses

Among the biotic and abiotic factors examined, the total species richness is by far the strongest predictor of alien species richness patterns (Table 1, Figure 1b). When analyzed by itself, the total species richness explained 27.9% of the variance of alien species richness.
The second strongest predictor was landscape diversity, quantified as the number of different Corine land cover classes observed in the area, using the finest thematic resolution of Corine to maximize the information content (Table 1). The third strongest predictor—when analyzed in isolation—was the area covered by artificial surfaces (i.e., urban areas and transportation network). Similar results were observed for temperature seasonality and area covered by agriculture that, in isolation, were decent predictors of alien species richness but offered little additional content to the combined model. On the other hand, taking into account the Bonferroni adjustment, wetland areas were not significantly correlated to alien species richness (Table 1). Given that several of the factors that shape alien species richness also shape native species richness (Table 1), we built the model with all predictors to disentangle the relative contribution of the abiotic factors once species richness was included in the model.
The combined model with all predictors displayed R2 64.7%. However, three of the predictors—precipitation seasonality, wetland area, and landscape fragmentation—were not significant and were removed from the final model. The final model included seven environmental factors and displayed R2 62.8% (Figure 2). By far the most important driver was total species richness, which, if removed, the model of the remaining factors displayed R2 only 32.2% (Table 2). No other factor caused such a drop in the explanatory power of the model if removed. The effect of total species richness on alien species richness is not linear (Figure 2), but initially, an increase in total species richness is associated with a sharp increase in alien species richness, but as the total species richness is higher, the effect is milder. The effect of the mean annual temperature is almost linear, with higher alien species richness observed in the hottest areas. Temperature seasonality has a linear effect, with higher species richness in areas with higher seasonality (these areas were also characterized by higher annual precipitation given the strong linear correlation—R2 = 79%—of the two climatic factors in our data). Among the different categories of land use, artificial surfaces and agricultural lands displayed a linear effect with increasing alien species richness in areas with a greater proportion of the land appropriated for human use (Figure 2). Vegetation displayed the opposite trend, with lower alien species richness in areas dominated by natural and semi-natural vegetation (Figure 2). Landscape diversity—quantified as the number of Corine land cover classes—displayed a positive, almost linear, association with alien species richness (Figure 2).
In the combined model that explains most of the variance of alien species richness, the leading factor is native species richness. But the effect of native species richness might “mask” important environmental predictors for alien species richness. Thus, we repeated the model for only abiotic factors, and the new model displayed R2 32.2%. More importantly, the role of some predictors shifted (Figure 3). Temperature seasonality increased in importance, and its effect appeared strongly negative and linear. Also, the areas covered by vegetation appear to have a less important role, but with maximum alien species richness at intermediate levels. For the other factors, the exact shape of their effect changed, but the general pattern remained. Artificial surfaces (such as urban areas and transport networks) appear to exert an even stronger influence.
These results lead to the next question on what explains this strong association between native and alien species richness patterns. To deeper explore this association, we examined the role of the different environmental factors in shaping native species richness and how they contrast to their role in shaping alien species richness (Table 1). The mean annual temperature is the strongest predictor, with native species richness being higher at lower temperatures, contrary to alien species richness, which was highest in warm temperatures. Precipitation was among the strongest predictors of native species richness. Among the landscape factors, only vegetation played a more important role in native species richness than in alien species richness (Table 1). Landscape diversity and fragmentation—which were important predictors for alien species richness—were weakly associated with native species richness, and more importantly, native species richness increased with vegetation coverage and decreased with agricultural land, while the opposite is true for alien species richness.
Both facets of plant species richness displayed similar strength in their association with environmental factors when examined in combination (Table 2). However, landscape factors were far more important predictors of alien plants species richness than of native species richness, while climatic factors were more important predictors of native plants species richness than of alien species richness (Table 2).

4. Discussion

One of the main reasons why so many hypotheses proliferate in the literature on invasion biology is that most of these hypotheses are not mutually exclusive, and many of the observed patterns could be attributed to more than one of them. This is the case with our findings, too. The strongest support seems to be for the biotic acceptance hypothesis, but several others (such as environmental heterogeneity, empty niche, human commensalism, disturbance, and propagule pressure) could not be rejected and also play a role—even if it is a secondary one.

4.1. Inference about the Mechanisms Underlying Alien Species Richness Patterns

At the relatively coarse scale of our analysis, the most apparent driver of alien species richness patterns is native species richness. The positive, even though not linear, association between the two facets of biodiversity is in accordance with the predictions of the biotic acceptance hypothesis that areas that could support more native species could also support more alien species [12,33]. This pattern has often been observed at coarse scales, like here, while at fine scales, the opposite has been observed, a phenomenon known as the invasion paradox [13,34]. In the Italian flora, there is no significant relationship between native and alien diversity at fine scales, but at the coarse scale, there is a positive association [35]. But in the case of Greek plant diversity, this is not a scale-dependent phenomenon since a positive association between native and alien species richness was also observed in fine-scale biodiversity data from the protected areas of the Greek Natura 2000 network [36]. This association means that biodiversity hotspots include a diversity of alien species, and this may pose a threat for native species [37]. So, it becomes important to comprehend what drives this positive association.
Environmental heterogeneity is a potential explanation, i.e., different environmental conditions may favor the persistence of the different groups of species across the landscape and thus promote coexistence. Our results seem to offer some support for this mechanism. Both native and alien species richness are positively associated with landscape heterogeneity (quantified as the number of different Corine land cover classes), but this is a stronger association for alien species richness than for natives. Even after accounting for the role of native species richness, landscape diversity contributed toward explaining the alien species richness patterns. But this landscape-level heterogeneity can only be part of the explanation, since this positive relationship between native and alien species richness also holds for local—within habitat—diversity [36].
Another mechanism that has been proposed to explain the association between native and alien diversity is that both groups of species display similar environmental preferences, or the environmental factors restricting the native species may also restrict the alien species [38,39]. There is currently evidence both in support [40] and against this mechanism [41]. Our results are not in accordance with this mechanism since we found that although this similarity holds for certain factors (like temperature seasonality), for most factors examined here (e.g., annual temperature and human-dominated land uses) important differences became apparent. Climate plays a more important role in shaping native species richness than alien species richness, while landscape configuration (and mainly human-dominated land uses) is far more important for alien species richness patterns than for native ones. This finding is in accordance with global patterns that socio-economic factors are more important drivers of alien species patterns than native species patterns [42]. Even more importantly, in our case, it is not only the relative importance of the different factors but also the way the different factors affect species richness that we observe contrasting effects for native and alien species. Native species richness is positively associated with natural vegetation cover across the landscape and negatively associated with agricultural land cover and mean annual temperature. The opposite was observed for alien species richness. Our findings are in accordance with patterns in Northern Italy, where agriculture favored alien plant species more than native plant species richness [43]. These patterns are especially troubling in the frame of climate change and how it might exacerbate the impact of alien plants on native flora in the not-so-distant future. Alien species are expected to increase their ranges in the foreseeable future as they have yet to reach equilibrium and some alien species whose expansion is limited by climate are expected to exhibit greater rates of establishment under changes in temperature [44].
So, if aliens and natives show preference for different environmental conditions—in a sense, different niche dimensions—then we might speculate that alien species may be able to occupy some niche space that the native species did not exploit and thus find an opportunity to establish, avoiding competition [45]. Furthermore, one may argue that these differences are in line with the predictions of the limiting similarity hypothesis that aliens perform better in areas where they differ from native species. But our findings should be considered as circumstantial evidence for these “empty niche” and “limiting similarity” hypotheses. And even if true, this is not an explanation of the positive native–alien species richness relationship. There needs to be something more to explain these results. A possible explanation may reflect that areas with greater resource availability can support more species, meaning more alien as well as more native species. In this study, we used landscape metrics as a proxy for resource diversity and found natives and aliens not to share preferences, but plants also use resources that are not reflected by the metrics used (e.g., soil nutrients). Therefore, it is possible that some resources that were not included in our analysis may play an important role in shaping diversity patterns and hold part of the puzzle. But this remains an open question.
The most often cited hypothesis that is also in accordance with our findings is the propagule or colonization pressure hypothesis, which focuses on the role of species introductions through human activities or natural processes [8]. This hypothesis predicts that the spread of alien species is facilitated by human transportation infrastructure, especially infrastructure enabling long-distance, even intercontinental transport such as ports and airports [7,46]. The patterns observed here are in accordance with such a prediction, since alien species richness is positively associated with the Corine land cover classes related to the transportation network (especially ports and airports), while native species richness is not associated. This finding is further supported at fine scales, where alien species richness increased towards the road network [36].
Another hypothesis emphasizes that species as aliens, living in close proximity to humans, are more likely to successfully establish [47]. Our results are in accordance with the predictions of this hypothesis since human-dominated land covers (like agricultural areas, and more importantly urban areas) favor alien species richness, while the opposite trend was observed for natural vegetation coverage. Further support for this argument is that most synanthropic ruderal species in Greece are alien [48]. This preponderance of aliens among weeds in the Greek flora is in accordance with the literature that the traits associated with weeds favor the establishment and spread of alien species [49].

4.2. Conservation Implications

Concludingly, the spatial patterns of alien species diversity highlight the multifaceted processes underlying the spread of alien species richness [50]. The strong positive association between alien and native species richness may be a sign for a potential problem for biodiversity conservation. This relationship is mediated by different mechanisms like environmental heterogeneity and speculative resource availability, but it does not appear to be due to native and alien species preferring the same environmental conditions. Especially given that native species appear to prefer cooler conditions and alien species seem to prefer warmer conditions, the ongoing climate change might synergistically affect Greek biodiversity in the near future.
The predicted future climatic conditions in the Mediterranean basin (more arid periods and higher temperatures) suggest that many of the native plant species will become extinct or migrate to higher altitudes and/or northern latitudes (wetter and cooler areas), while alien species will find conditions favoring their range expansion and population growth. For instance, the adaptation capacity of the widespread invasive alien species Solanum elaeagnifolium in various environmental conditions (e.g., drought, salinity, and competition), implies that it will possibly survive better than many native species [51,52,53], especially better than range-restricted and local endemics, even after destructive phenomena such as wildfires, which are predicted to increasingly happen in the region. For example, in Greece (an area highly affected by climate change in the Mediterranean basin), S. elaeagnifolium is recorded almost in any habitat type, even in protected areas and national parks and at altitudes up to 1200 m. These facts will allow in the future further expansion of this weed in terms of area and altitudinal zone, and rapid deterioration of natural habitats, cultural landscapes and relevant ecosystem services.
Alien species are closely associated with human-dominated land cover, while native species prefer more natural vegetation. This might indicate a tool for nature conservation in Greece at fine scales, i.e., one may argue for limiting human activities (including transportation networks) in biodiversity hotspots to limit the spread of alien species. Additionally, the study outcomes contribute to the national efforts for MAES implementation in Greece [54], providing spatially explicit information for drafting measures and actions for tackling impacts on ecosystem services due to alien species expansion (or invasion) and acting as a reference for ecosystem condition assessments under the national natural capital accounting efforts (e.g., alien species richness as an index for monitoring ecosystem condition) [55]. Hence, our work provides a coherent baseline for scientifically informed decisions on further management and policy actions in Greece, under the provisions of the EU Biodiversity Strategy, the EU Green Deal, and the EU’s new Nature Restoration Law, to combat alien and invasive alien species for preserving and restoring autochthonous ecosystems, biodiversity, and ecosystem services

Author Contributions

Conceptualization, A.K. and P.D.; methodology, A.K. and I.P.K.; formal analysis, A.K.; data curation, I.P.K., P.D., T.R., I.B. and A.S.; writing—original draft preparation, A.K.; writing—review and editing, all authors; funding acquisition, P.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research was partially funded by the European Commission LIFE Integrated Project, LIFE-IP 4 NATURA “Integrated Actions for the Conservation and Management of Natura 2000 sites, species, habitats and ecosystems in Greece”, Grant Number: LIFE 16 IPE/GR/000002.

Institutional Review Board Statement

This study did not require ethical approval.

Data Availability Statement

This analysis is based on publicly available data. Land use data are from the EU Corine land use land caver dataset. Climate data are from the WorldClim dataset. Alien diversity data are from the alien plants of Greece platform (www.alienplants.gr accessed on 8 September 2023).

Acknowledgments

We would like to acknowledge the scientists whose fieldwork contributed to the collection of the primary data analyzed here.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Alien plant species richness (a), and total plant species richness (b). In both panels, values are presented per 10 km × 10 km grid cell of the EEA (European Environment Agency) reference grid for Greece. The term “species” includes both plant species and subspecies.
Figure 1. Alien plant species richness (a), and total plant species richness (b). In both panels, values are presented per 10 km × 10 km grid cell of the EEA (European Environment Agency) reference grid for Greece. The term “species” includes both plant species and subspecies.
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Figure 2. Effect plot for the GAMM for the smoother functions of the different environmental factors as predictors of alien species richness. The model explained 59.8% of the alien species richness variance. The Generalized Additive Models were built with negative binomial distribution.
Figure 2. Effect plot for the GAMM for the smoother functions of the different environmental factors as predictors of alien species richness. The model explained 59.8% of the alien species richness variance. The Generalized Additive Models were built with negative binomial distribution.
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Figure 3. Effect plot for the GAMM for the smoother functions of the different environmental factors as predictors of alien species richness. The model explained 32.2% of the alien species richness variance. The GAMM was built with negative binomial distribution.
Figure 3. Effect plot for the GAMM for the smoother functions of the different environmental factors as predictors of alien species richness. The model explained 32.2% of the alien species richness variance. The GAMM was built with negative binomial distribution.
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Table 1. Summary statistics for the GAMMs describing the association of each environmental factor as driver of alien species richness. To account for spatial autocorrelation inflating significance we used the spatial coordinates as a correction in the GAMM approach. Since species richness are count data, we used GAMM with negative binomial distribution. To account for multiple comparisons, we used the Bonferroni attachment and considered it significant at only p < 0.004.
Table 1. Summary statistics for the GAMMs describing the association of each environmental factor as driver of alien species richness. To account for spatial autocorrelation inflating significance we used the spatial coordinates as a correction in the GAMM approach. Since species richness are count data, we used GAMM with negative binomial distribution. To account for multiple comparisons, we used the Bonferroni attachment and considered it significant at only p < 0.004.
Predictor Alien Species Richness
R2 as Single Predictor		Native Species Richness
R2 as Single Predictor
Native species richness27.9% (p < 0.0001)
Mean annual temperature10.9% (p < 0.0001)10.3% (p < 0.0001)
Temperature seasonality8.1% (p < 0.0001)13.4% (p < 0.0001)
Precipitation seasonality9.7% (p < 0.0001)7.1% (p < 0.0001)
Artificial surfaces area11.1% (p < 0.0001)3.2% (p < 0.0001)
Agricultural area8.2% (p < 0.0001)3.3% (p < 0.0001)
Vegetation area8.1% (p < 0.0001)9.0% (p < 0.0001)
Wetland area0.8% (p = 0.0328)0.0% (p = 0.3090)
Landscape diversity 15.1% (p < 0.0001)4.1% (p < 0.0001)
Landscape fragmentation6.6% (p < 0.0001)3.2% (p < 0.0001)
Transport network7.3% (p < 0.0001)0.2% (p = 0.1601)
Table 2. Summary statistics for the GAMMs describing the role of different sets of environmental factors as driver of alien and native species richness. To account for spatial autocorrelation inflating significance, we used the spatial coordinates as a correction in the GAMM approach. Since species richness are count data, we used GAMM with negative binomial distribution.
Table 2. Summary statistics for the GAMMs describing the role of different sets of environmental factors as driver of alien and native species richness. To account for spatial autocorrelation inflating significance, we used the spatial coordinates as a correction in the GAMM approach. Since species richness are count data, we used GAMM with negative binomial distribution.
PredictorsR2 for Alien Species Richness GAMM ModelR2 for Native Species Richness GAMM Model
Climatic factors15.9% (p < 0.0001)25.0% (p < 0.0001)
Landscape factors29.9% (p < 0.0001)18.0% (p < 0.0001)
Combined climatic and landscape factors32.2% (p < 0.0001)29.3% (p < 0.0001)
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Kallimanis, A.; Kokkoris, I.P.; Bazos, I.; Raus, T.; Strid, A.; Dimopoulos, P. What Insight Does the Alien Plant Species Richness in Greece Offer for the Different Invasion Biology Hypotheses? Diversity 2023, 15, 1067. https://doi.org/10.3390/d15101067

AMA Style

Kallimanis A, Kokkoris IP, Bazos I, Raus T, Strid A, Dimopoulos P. What Insight Does the Alien Plant Species Richness in Greece Offer for the Different Invasion Biology Hypotheses? Diversity. 2023; 15(10):1067. https://doi.org/10.3390/d15101067

Chicago/Turabian Style

Kallimanis, Athanasios, Ioannis P. Kokkoris, Ioannis Bazos, Thomas Raus, Arne Strid, and Panayotis Dimopoulos. 2023. "What Insight Does the Alien Plant Species Richness in Greece Offer for the Different Invasion Biology Hypotheses?" Diversity 15, no. 10: 1067. https://doi.org/10.3390/d15101067

APA Style

Kallimanis, A., Kokkoris, I. P., Bazos, I., Raus, T., Strid, A., & Dimopoulos, P. (2023). What Insight Does the Alien Plant Species Richness in Greece Offer for the Different Invasion Biology Hypotheses? Diversity, 15(10), 1067. https://doi.org/10.3390/d15101067

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