# The Anthropocene biogeography of alien birds on islands: drivers of their functional and phylogenetic diversities

Clara Marino, Lysandre Journiac, Chunlong Liu, Jonathan M Jeschke, Céline Bellard

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Clara Marino, Lysandre Journiac, Chunlong Liu, Jonathan M Jeschke, Céline Bellard. The Anthropocene biogeography of alien birds on islands: drivers of their functional and phylogenetic diversities. Ecology Letters, 2024, 27 (6). hal-04510847v2

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1 **Title page for:**

2 **The Anthropocene biogeography of alien birds on islands: drivers of their**

3 **functional and phylogenetic diversities**

4

5 **Authors:**

6 **Clara Marino**¹,²\* (claramarino665@gmail.com)

7 **Lysandre Journiac**¹\* (lysandre.journiac@edu.mnhn.fr)

8 **Chunlong Liu**³ (liuchunlong@ouc.edu.cn)

9 **Jonathan M. Jeschke**⁴,⁵,⁶ (jonathan.jeschke@gmx.net)

10 **Céline Bellard**¹ (celine.bellard@universite-paris-saclay.fr)

11 **Affiliations:**

12 ¹Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Systématique Evolution, Gif-sur-

13 **Yvette, France**

14 ²FRB-Cesab, 5 rue de l'école de médecine 34000 Montpellier

15 ³The Key Laboratory of Mariculture, Ministry of Education, College of Fisheries, Ocean

16 **University of China, Qingdao 266003, China**

17 ⁴Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Berlin, Germany

18 ⁵Institute of Biology, Freie Universität Berlin, Berlin, Germany

19 ⁶Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Berlin, Germany

20 \*Authors contributed equally

21 **Corresponding author:** **Clara Marino** (claramarino665@gmail.com)

22

23 **Short running title:** Biogeography of alien bird diversities

24
**Keywords:** alien birds, biodiversity drivers, biological invasions, functional diversity, islands, phylogenetic diversity.

**Type of article:** Letters

**Number of words in the abstract:** 147

**Number of words in the main text:** 4937

**Number of references:** 66

**Number of figures:** 4

**Number of tables:** 1

**Author Contributions:**

CM: Conceptualization, Data Curation, Formal analysis, Visualization, Writing – original draft, Writing – review & editing

LJ: Data Curation, Formal analysis, Writing – original draft, Writing – review & editing

CL Conceptualization, Writing – review & editing

JJ: Conceptualization, Writing – review & editing

CB: Conceptualization, Funding Acquisition, Writing – review & editing

**Competing Interest Statement:** The authors declare no competing interest.

**Data accessibility statement:** The data and codes that support our analyses are available from Zenodo (https://zenodo.org/doi/10.5281/zenodo.10797742) and GitHub (https://github.com/claramarino/biogeo_alien_FD_PD). Data include all variables used in the SEM, such as alien diversity values on each island for the three facets (i.e., taxonomic, phylogenetic and functional) as well as insular anthropogenic, biotic and geographic contexts.
50 Main document for:

51

52 The Anthropocene biogeography of alien birds: drivers of their functional
53 and phylogenetic diversities on islands

54

55 Clara Marino*, Lysandre Journiac*, Chunlong Liu, Jonathan M. Jeschke, Céline Bellard

56 *Authors contributed equally

57 Corresponding author: Clara Marino

58

59 Abstract

60 A branch of island biogeography has emerged to explain alien species diversity in the light of
61 the biogeographic and anthropogenic context, yet overlooking the functional and phylogenetic
62 facets. Evaluating alien and native birds of 407 oceanic islands worldwide, we built structural
63 equation models to assess the direct and indirect influence of biotic, geographic, and
64 anthropogenic contexts on alien functional (FD) and phylogenetic diversity (PD). We found
65 that alien taxonomic richness was the main predictor of both diversities. Anthropogenic
66 factors, including colonization pressure, associated with classic biogeographical variables also
67 strongly influenced alien FD and PD. Specifically, habitat modification and human
68 connectivity markedly drove alien FD, especially when controlled by taxonomic richness,
69 whereas human population size, gross domestic product, and native PD were crucial at
70 explaining alien PD. Our findings suggest that humans not only shape taxonomic richness but
71 also other facets of alien diversity in a complex way.

72
73

# INTRODUCTION

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Natural eco-evolutionary processes have shaped insular ecosystems and biota for millions of years. Since MacArthur and Wilson's book *The Theory of Island Biogeography* (MacArthur & Wilson 1967), there has been a growing interest in estimating and predicting species taxonomic richness on islands using geophysical factors (Whittaker *et al.* 2017). However, human arrivals on islands disturbed the natural processes by accelerating the introduction of alien species (Fernández-Palacios *et al.* 2021). A new branch of insular biogeography in the Anthropocene has thus emerged to study the diversity of alien species, such as birds, mammals, and plants (van Kleunen *et al.* 2015; Capinha *et al.* 2017; Dawson *et al.* 2017; Dyer *et al.* 2017a; Seebens & Kaplan 2022). This branch has shown several consistent patterns with the theory of island biogeography (e.g., species-area relationship) (Baiser *et al.* 2018; Blackburn *et al.* 2021; Matthews *et al.* 2023). However, the classic species-isolation relationship (i.e., remote islands contain less species) has weakened due to more alien species established in remote islands (Helmus *et al.* 2014; Moser *et al.* 2018).

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Previous studies of alien diversity on islands have focused on only one facet of diversity (i.e., taxonomic diversity). There are only few studies assessing functional and phylogenetic diversities of native and alien biota with a special focus on diversity-area relationships (Matthews *et al.* 2023; Sayol *et al.* 2021; Soares *et al.* 2022), and to our knowledge, there is no study to date that investigated how the multiple facets of alien diversity on islands, including functional (FD) and phylogenetic (PD) diversity, are affected by biogeographic and anthropogenic drivers. This knowledge gap is surprising, as both FD and PD are crucial to understand invasion dynamics and properly explore island biogeography in the Anthropocene.

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Functional diversity represents the set of ecological strategies hosted by an assemblage (Mouillot *et al.* 2013), reflecting the ecological assembly rules of this assemblage (Mouchet *et al.* 2013).
al. 2010). By studying alien FD, we can determine how alien species mediate their response to disturbances and contribute to ecosystem functioning given they may replace native species (Soares et al. 2022). Phylogenetic diversity (PD) captures the evolutionary history of species, their features and future options (Faith 1992; Purvis et al. 2019). Because alien species are introduced by humans for specific purposes (Dyer et al. 2017a), we can expect that alien PD is not only affected by biogeographical factors but also by human ones, and mediated by native biota. By identifying the factors determining alien FD and PD, we could anticipate the fate of insular diversity in a disturbed environment and provide guidelines to effective conservation strategies. Our aim here is to provide the first global evaluation of the drivers of FD and PD patterns for island alien birds, in one single analytical framework.

Birds are taxonomically well described and are the object of the most comprehensive resource on the global distribution of alien species (Jetz et al. 2012; Dyer et al. 2017b; Tobias et al. 2021). During European colonization, many birds were intentionally introduced, particularly specific families (e.g., Galliniformes) originating from Western Europe (Cassey et al. 2015), and species with peculiar traits (e.g., diurnal and granivorous birds foraging on the ground and in artificial terrestrial habitats (Soares et al. 2021). This period resulted in numerous introductions on remote islands marked by a taxonomic selection for probability of alien establishment (Lockwood 1999), representing a biased sample of global avian evolutionary history and ecology. Moreover, Dyer et al. (2017a) showed that the identity of introduced birds and the relative importance of colonization pressure, i.e., the number of species introduced to an area (Blackburn et al. 2020), varied through time. Birds are thus an excellent model for exploring global distribution of FD and PD of alien species.

Here, we investigate the spatial pattern of FD and PD for alien birds and their drivers on 407 oceanic islands worldwide. Notably, we aim to test how 15 island contextual variables
related to the geographic (e.g., area, distance to mainland, elevation), biotic (i.e., taxonomic richness, FD and PD of native birds), and anthropogenic (e.g., human population size, connectivity, habitat modification, colonization pressure) contexts shape alien bird FD and PD. We expect that species richness of alien assemblages will partially drive alien FD and PD. Moreover, we seek to determine the effects of insular contexts on alien FD and PD which may be mediated by species richness. We further explore how critical the anthropogenic context is compared to the biogeographic context to explain alien diversities. To investigate these effects, we apply structural equation models (SEMs) by defining a priori directional links between the contextual variables and alien diversities (Table 1; Table S1 describes the links connecting contextual variables). Finally, we calculate the deviations of FD and PD from expected values given the taxonomic richness, allowing us to detect the drivers of the relative variation of FD and PD beyond taxonomic richness (i.e., standardized effect size (SES) of FD and PD) (Bach et al. 2022).

## 134 MATERIAL AND METHODS

### 135 Alien bird diversities on oceanic islands

Study islands and species. Our dataset is based on the oceanic islands from Weigelt et al. (2013), defined as land masses larger than one km² not connected to the mainland during the last glacial maximum. Alien assemblages were obtained by overlapping the distribution of current established alien bird populations from the global avian invasion atlas (GAVIA) (Dyer et al. 2017b) and the oceanic island contours from GADM (http://www.gadm.org/version1). We restricted our dataset to oceanic islands that harbored at least four alien birds (n = 407 islands, for a total of 188 alien bird species), which was the minimum number of species to calculate FD on one island.
Functional and phylogenetic diversities. We defined an alien assemblage as the pool of all alien birds with an established population on an island. Alien bird FD of an island was the ratio between the convex hull encompassing species from the alien assemblage and the convex hull encompassing the global bird pool in a three-dimensional trait space (Mouillot et al. 2013). To calculate alien FD, we collected seven species-level traits related to morphology (i.e., beak length, beak depth, hand-wing index, body mass) and ecological preferences (i.e., trophic level, foraging niche and habitat breadth) for 10,862 bird species from AVONET (Tobias et al. 2021) and IUCN (2022). Then, we reduced the dimensionality of the species-trait matrix by computing a Principal Coordinate Analysis (PCoA) on the Gower's distance between species. We finally obtained a synthesized 3D-trait space representing 54.1% of the total variation among bird species (see Supporting text, Tables S2, S3 in SI for more details on functional space computation). Alien FD was computed for each island using the *alpha.fd.multidim* function from the *mFD* package (Magneville et al. 2021). We calculated alien PD as the minimum total length of all phylogenetic branches required to span all alien birds in the assemblage on a phylogenetic tree. Phylogenetic trees were extracted from VertLife database (https://vertlife.org), and PD was calculated on 1,000 trees using the *pd* function from the *picante* package (Kembel et al. 2010).

*Deviation from taxonomic diversity.* As we expect both FD and PD depend on alien taxonomic richness, we also computed standardized effect size indices (SES-FD and SES-PD) following Bach *et al.* (2022) to exclude the effect of alien taxonomic richness from these indices and explore the drivers of the relative variation of FD and PD. To do so, we performed null models using a matrix swap randomization by recalculating FD and PD (on 100 phylogenetic trees) on 100 randomly generated island-species matrices, while keeping a constant number of species per assemblage. These random assemblages were simulated on the global pool of alien birds documented in GAVIA (n = 952) with each species having the same
chance to become alien in each of the islands. SES indices were calculated as

$$SES = \frac{\text{observed value} - \text{mean}(\text{simulated values})}{\text{standard deviation}(\text{simulated values})}.$$ Negative values of SES indicate a lower value FD

or PD than expected by chance for an equal taxonomic richness, representing a more clustered assemblage in terms of traits or evolutionary history.

## 173 Potential drivers of functional and phylogenetic diversities of alien birds on islands

174 *Geographic variables.* We extracted the geographic variables for all islands from Weigelt *et al.* (2013). We retrieved three variables related to habitat heterogeneity (i.e., *Latitude, Area, Elevation*) and two variables linked to isolation (i.e., *Distance to the continent* and *Surrounding land mass*). Since native and alien bird diversities vary regarding geographic regions (Holt *et al.* 2013; Dyer *et al.* 2017a), we also classified each island into the corresponding zoogeographic region delineated by Holt *et al.* (2013). For islands without information on the zoogeographic region (n = 260), we attributed them to the closest region (Fig. S1).

182 *Biotic variables.* To account for the insular biotic context, we calculated the taxonomic richness of native birds for each island by computing the spatial overlap between the native ranges of all birds in the world (Birdlife International 2020) and the islands. We also calculated native FD and PD following the same methodology as for alien species.

186 *Anthropogenic variables.* We compiled seven variables associated with the anthropogenic context of each island. *Population size* was calculated as the sum of human population counts in the area of each island using the CIESIN database (2018). *Gross domestic product (GDP)* was calculated as the sum of all GDP values in the cells falling into each island using the data from Wang & Sun (2022). *Human connectivity* was calculated by mirroring the surrounding landmass as a metric of human isolation of each island. We summed each island's number of ports (https://data.humdata.org/dataset/world-port-index) and airports
193 (http://www.partow.net/miscellaneous/airportdatabase/) within the island and in a buffer of
194 100 km around the perimeter of the island. Finally, we retrieved two metrics related to habitat
195 modification by human activities (Theobald *et al.* 2020). *Static habitat modification* refers to
196 the median value of the current state of habitat modified by humans in 2017, while *Change
197 habitat modification* depicts the dynamics of habitat modifications between 1990 and 2015.
198 Both variables were aggregated at the island scale as the median of the values of habitat
199 modification. Using the GAVIA dataset, we also retrieved information of *Colonization
200 pressure* (i.e., the total number of alien species introduced to each island) for 96 islands, and
201 of *Time since first introduction* for 83 islands (see Supporting text for details on the method).

202 A priori hypotheses

203 We set 17 hypotheses to assess the links among the different variables (Table S1), including
204 10 hypotheses of direct links between absolute and relative values of alien diversities and the
205 insular contexts (Table 1). For instance, larger and more remote islands are known to host a
206 higher number of alien species, following known species-area and reverse species-isolation
207 relationships (Blackburn et al. 2016; Moser et al. 2018). Besides the absolute values of
208 FD/PD, we also seek to understand the variation and the drivers of FD/PD that are not
209 explained by species richness (i.e., SES-FD/PD). For instance, islands containing
210 heterogeneous habitats are the place for hosting species with more diversified ecological
211 strategies (Kadmon & Allouche 2007) and hypothetically more FD than expected given their
212 taxonomic richness (positive SES-FD). Moreover, native communities are likely to exert a
213 biotic filter on alien species and we can hypothesize lower SES-FD/PD than expected, if
214 competition or human selection exert a filter on alien species.

215 Statistical analyses

216 All statistical analyses were conducted in R (version 4.2.1) (R Core Team 2022).
To assess the direct, indirect, and total effects of biogeographic, anthropogenic, and
biotic factors on alien bird diversities, we performed SEMs using the *piecewiseSEM* package
(Lefcheck 2016). We built four SEMs on the 407 islands to explain each of the endogenous
variables related to alien diversity, i.e., alien FD, PD, SES-FD, and SES-PD, using our set of
*a priori* hypotheses (Tables 1, S1), excluding *Colonization pressure* and *Time since first
introduction* due to the existence of missing data in the two variables. We conducted models
with and without those two variables on sub-samples of islands (n=96 and n=83, respectively,
when data were available) to compare the effects of those variables on the outputs
(Supplementary text). All variables with a right-skewed distribution were log-transformed
(Area, Distance to the continent, Surrounding landmass, Elevation, Native richness, Native
PD, Native FD, Alien richness, Alien PD, and Alien FD), and *Latitude* was converted as an
absolute value. Finally, we scaled all the variables (μ = 0, sigma = 1) to get comparable
effects.

For each endogenous variable (i.e., a variable supposedly explained by one or several
exogenous variables), we derived a linear mixed-effects model, including the zoogeographic
region as a random effect. The SEMs were then built upon these individual linear mixed-
effects models (*psem* function from *piecewiseSEM* package). We evaluated SEM fit using
Fisher's C statistic and considered it incomplete if the associated P-value was below 0.05. In
the case of an incomplete model, we recursively added potential missing paths (i.e., paths that
were not included in the initial model because lacking any causal relationship), based on
pairwise tests of directed separation on unstated relationships between variables in the *a priori*
model (*dSep* function from *piecewiseSEM* package). The four final models had a Fisher's C of
41.5 (p = 0.24) for FD, 43.6 (p=0.18) for PD, 50.8 (p=0.12) for SES-FD, and 40.9 (p=0.19)
for SES-PD. They contained 51 paths between explanatory and endogenous variables, and a
correlated error was specified between anthropogenic variables and native biotic variables.
We analyzed the results of the models by retrieving the R² associated with each endogenous variable. As we used linear mixed-effects models, R² values were decomposed into marginal (accounting for fixed effects) and conditional (accounting for both fixed and random effects) R². Finally, we derived the explanatory variables' direct, indirect, and total effects on the response variables by using a non-parametric bootstrapping method (n = 10,000 samples) through the *bootEff* function from the *semEff* package (Murphy 2022).

## 249 RESULTS

### 250 Functional and phylogenetic diversities of alien birds

Functional and phylogenetic diversities of alien birds varied markedly across islands worldwide (Fig. 1). The Novozelandic and Hawaiian regions harbored islands with the higher FD and PD values, while alien birds in Saharo-Arabian, Indo-Malayan or Sino-Japanese regions had a lower diversity (Fig. 1A). We also observed a strong spatial variation of FD and PD values within regions among islands (e.g., Papua-Melanesian and Novozelandic) (Fig. 1B, C). Overall, FD and PD of alien birds were highly correlated across all islands (Pearson's correlation = 0.95, *p* < 0.001, Fig. S2A), but considering each region separately, we found varying shapes of relationships between both metrics (Fig. S2B). Both diversity facets were also highly correlated with alien taxonomic richness (Pearson's correlation = 0.94 for FD, 0.96 for PD). After controlling for alien taxonomic richness, we found that both SES-FD and SES-PD were significantly smaller than zero (Student tests, respectively, mean = -0.92, t = -33.6, *p* < 0.001; mean = -0.89, t = -13.6, *p* < 0.001). Thus, on average and especially in the Novozelandic region, alien assemblages were less phylogenetically and functionally diversified than expected from random assemblages of birds with the same taxonomic diversity (Fig. 2; Fig. S3). By contrast, assemblages from the Oriental, Panamanian and
266 Saharo-Arabian regions had positive SES-PD values close to zero, representing a PD that was
267 nearly expected given the taxonomic richness (Fig. 2).

268 Drivers of alien diversities

269 Six variables had a significant total effect on alien FD (R² marginal = 0.60), namely alien
taxonomic richness, native taxonomic richness, static habitat modification, human
270 connectivity, elevation, and distance to continent (confidence intervals (CI) at 95% not
271 crossing zero, Fig. 3A, 4A). Eight variables had a significant total effect on alien PD (R²
272 marginal = 0.90), namely alien taxonomic richness, native PD, human connectivity,
273 population size, GDP, surrounding landmass, distance to continent, and area (Fig. 3B, 4B).
274

275 Overall, alien taxonomic richness had the largest total effect on alien FD and PD
276 (mean total effect = 0.58 and 0.79, respectively) followed by the geographic context (mean
277 combined total effect = 0.40 and 0.57), the anthropogenic context (mean combined total effect
278 = 0.39 and 0.44) and, to a lesser extent, by the biotic context (mean combined total effect =
279 0.15 and 0.15) (Table S4). Moreover, when anthropogenic variables were included in the
280 SEM, the R² of alien FD and PD were identical but the R² of alien taxonomic richness
281 increased by 12 to 15% compared with the SEM with biogeographical variables only (Fig.
282 S4).

283 Alien taxonomic richness had a substantial direct effect on both alien FD (95% CI:
284 [0.46; 0.72]; Fig. 3A, 4A) and PD (95% CI: [0.76; 0.90]; Fig. 3B, 4B). By contrast, native
285 taxonomic richness had a total negative effect on alien FD (95% CI: [-0.22; -0.04]; Fig. 3A)
286 and a weak negative effect on alien PD (95% CI: [-0.22; 0.04]; Fig. 3B). Moreover, native PD
287 had a moderate direct negative effect on alien PD (95% CI: [-0.20; -0.03]; Fig. 3B), whereas
288 native FD had no significant effect on alien FD (Fig. 3A).
Regarding anthropogenic drivers, connectivity, population size, and GDP had a total positive effect on alien PD mediated by positive effects on alien taxonomic richness. By contrast, connectivity and static habitat modification positively affected alien FD (Figs. 3, 4). Human connectivity was the anthropogenic driver with the most considerable total effect on both alien FD and PD (95% CI: [0.04; 0.23] and [0.04; 0.23], respectively; Figs. 3, 4). When considering colonization pressure (and time since first introduction) on the subset of 96 (83) informed islands for this variable, colonization pressure had the strongest total effect on alien FD and PD among anthropogenic drivers (Fig. S5), while time since first introduction had no effect (Fig. S6). The presence of colonization pressure in the predictors led to a decrease in the importance of the other anthropogenic effects compared to models without it, for both alien FD and PD. However, confidence intervals largely overlapped in the two types of models for all predictors.

Biogeographic variables posed different effects on alien FD and PD. Distance to continent had a positive direct effect on alien taxonomic richness and a positive indirect effect on both alien FD and PD (95% CI: [0.11; 0.30] and [0.10; 0.28], respectively; Figs. 3, 4). Island area had a total positive effect on alien PD (95% CI: [0.06; 0.17]), but not on alien FD, while island elevation had a positive direct effect on alien FD (95% CI: [0.08; 0.22]), but not on alien PD (Fig. 3). The total effect of biogeographic variables was similar in models accounting for colonization pressure. Moreover, the zoogeographic regions included as a random effect increased the explanatory power of the SEMs (conditional R²: 0.74 for FD; 0.93 for PD).

The final models obtained for SES strongly differed from the ones obtained for FD and PD values. While alien taxonomic richness remained a major driver of SES-FD and SES-PD (so when controlled by taxonomic richness), it had a strong negative direct effect on both SES-FD and SES-PD (Fig. 3). This means that alien bird assemblages with higher richness
314 are more likely to be phylogenetically and functionally clustered. Anthropogenic variables
315 had a more substantial influence on the SES than biogeographic variables (Fig. 3), with
316 evidence of a total negative effect of human connectivity on SES-FD and SES-PD and of
317 static modification on SES-FD. Among biogeographic variables, only island area showed
318 moderate evidence of a total negative effect on SES-FD (Fig. 3).

319

320 DISCUSSION

321 Global spatial variation of alien diversities

322 Our study provided important insights on the global spatial variation of alien diversities.
323 Relative values of alien FD and PD varied across and within regions. The Novozelandic and
324 Hawaiian regions harbored the highest levels of alien bird FD and PD, as well as some islands
325 of Papua-Melanesia. Previous studies have pointed out the specificity of the Hawaiian
326 archipelago related to its extremely high richness of alien plant species (Denslow et al. 2009;
327 Wohlwend et al. 2021), as well as the long history of New Zealand for dealing with biological
328 invasions (Simberloff 2019). Those regions are well-known hotspots of invasions regarding
329 taxonomic (Bellard et al. 2017; Dawson et al. 2017) and phylogenetic diversity (Baiser et al.
330 2018), but this is the first time it is also demonstrated for the different facets of diversity at the
331 global scale. Looking at SES, we found that islands from the Novozelandic region bear
332 assemblages of aliens with less phylogenetic diversity than expected from a random
333 community assembly, as highlighted by Baiser et al. (2018), but also a poorer functional
334 diversity. This pattern can be explained by the invasion history of those islands for which
335 most of their exotic species were imported from Britain and belong to few families
336 (Blackburn & Duncan 2001; Baiser et al. 2018). Moreover, some hotspots of alien bird FD
337 and PD were not previously highlighted when focusing only on taxonomic diversity,

338 including some islands of the Papua-Melanesian and Panamanian regions.

339

340 **The relative contribution of biogeographic, anthropogenic and biotic factors**

341 While alien taxonomic richness most strongly affected alien FD and PD, both anthropogenic

342 and biogeographic contexts also had remarkable and comparable total effects on these

343 diversities. Anthropogenic variables exceed by far the effects of biogeographic variables

344 when considering SES-FD and SES-PD. This revealed that besides classical biogeographic

345 variables, the anthropogenic context is highly important to understand the absolute (FD, PD)

346 and relative (SES-FD, SES-PD) richness of birds. Therefore, neglecting anthropogenic

347 variables significantly decreased our ability to explain the observed alien diversity on islands.

348

349 **Including anthropogenic factors to fully address the diversity patterns of alien species**

350 Our results suggest a substantial effect of anthropogenic factors on alien FD and PD, which

351 have also been documented for alien species from several taxa on continents (Pyšek *et al.*

352 2010). First, we found a strong positive effect of human connectivity on absolute and relative

353 alien bird richness, indirectly affecting alien FD, PD, SES-FD and SES-PD. Human

354 connectivity reshapes environmental barriers between isolated places, the distance to a human

355 facility that introduces species on islands being a primary determinant of alien distribution

356 (Gleditsch *et al.* 2023). Human connectivity is also a proxy of colonization pressure, a critical

357 factor in alien taxonomic richness (Blackburn *et al.* 2020). Indeed, when included, we found

358 that colonization pressure was the most important anthropogenic factor in the SEMs

359 contributing to alien FD and PD, and it reduced the direct effect of connectivity on alien

360 species richness and thus the indirect effect on alien PD (Figure S5).
Second, habitat modification positively influenced alien taxonomic richness and indirectly alien FD. Habitats with stronger human activities are considered more favorable for alien species establishment, partly because alien species do not have to compete with native species that are excluded from those disturbed habitats (Sol et al. 2022). Moreover, aliens adapt more to human-associated habitats due to their proximity and evolution with societies. The effect of habitat modification on FD rather than PD supports the idea that alien species exploit environmental niches in disturbed environments that differ from native ones (Soares et al. 2021).

We also observed contrasting effects of specific factors on SES-PD and SES-FD, which were negatively affected by static habitat modification and connectivity. This suggests that apart from increasing the number of alien species, a high human presence implies a clustering of alien species in terms of traits and evolutionary history. At some point, with the introduction of alien birds, a plateau is reached for alien FD and PD, and the supplemental addition of species does not lead to further functional or phylogenetic novelties. This also suggests that humans tend to bring the same type of species in terms of evolutionary history and ecological characteristics. Combined with native extinctions, alien species introductions favor the global homogenization of insular biota on the multiple facets of diversity (Sobral et al. 2016; Baiser et al. 2018; Sayol et al. 2021; Soares et al. 2022). The introduction of alien species might thus reinforce the observed FD-area non-linear relationship (i.e., the increase in area and native species richness does not imply a proportional increase in trait space), with even more species clustered in already well-represented parts of the trait space (Karadimou et al. 2016; Matthews et al. 2023).

**Native communities as a weak biotic filter to alien diversities**
Our study confirms that the biotic context (native taxonomic richness or their associated FD and PD) has a weaker influence on invasion success than anthropogenic or biogeographic contexts at this scale (Redding et al. 2019). For instance, the SEM analysis showed that native taxonomic richness had a direct positive effect on alien PD counterbalanced by an indirect negative effect through native PD. We also found a negative effect of native SES-PD on alien SES-PD (and a weak negative effect on alien SES-FD), suggesting that when native species are evolutionarily or ecologically clustered (negative SES), alien species are more widespread across the tree of life and trait space (positive SES). Despite previous works showing evidence of filters exerted by native communities on alien ones (Jeschke & Heger 2018), our study confirms the importance of abiotic and anthropogenic factors for shaping alien diversities.

## Biogeographic factors continue to drive alien diversities

Distance to the closest continent was the strongest biogeographic driver explaining alien FD and PD, and also negatively affected alien SES-FD and SES-PD. Remote islands tend to contain more alien species than closer islands following a reverse species-isolation relationship (SIR), and thus a more diverse alien assemblage regarding traits or evolutionary history. Our results are consistent with previous findings for other groups like plants or reptiles (Blackburn et al. 2016; Moser et al. 2018; Gleditsch et al. 2023). Interestingly, this pattern has never been confirmed for alien birds, with contrasting effects of remoteness on alien bird richness, either a negative indirect effect through native taxonomic richness (Blackburn et al. 2016), no effect (Moser et al. 2018), or a positive effect (Blackburn et al. 2008). We can confirm that reverse SIR is also validated for alien birds globally, thanks to the SEM analysis. For native birds, the original SIR was verified: taxonomic richness on islands declined with distance to continent (Fig. S7). The negative indirect effect of distance to
410 continent on alien SES-FD and SES-PD suggests that remote islands with higher alien species
411 richness also tend to contain more redundant species in terms of traits or evolutionary history.
412 Yet we also found a positive direct effect of distance to continent on alien SES-FD, meaning
413 that, independently of species richness, islands farther from continents favor more diverse
414 traits. This could be due either to humans that select birds with different characteristics for
415 various purposes, or to a high competition with congeners on remote islands, favoring the
416 establishment of more diverse traits.

417 We additionally found that both surrounding land mass and area positively affected
418 alien PD indirectly through alien taxonomic richness but had no total effect on alien FD. The
419 overall effect of island area was weak, suggesting that this is not a primary determinant in
420 alien bird diversities, contrasting with previous studies (Blackburn et al. 2008, 2016). The
421 log-log species-area relationship stands for alien species in many taxa, such as plants (Rojas-
422 Sandoval et al. 2020) and insects (Mally et al. 2022). Still, the slope of the relationship is
423 steeper than for native species with anthropogenic variables complementing the effect of
424 biogeographic ones (Rojas-Sandoval et al. 2020), the available area for alien species to invade
425 islands being non-saturated (Guo et al. 2020). Another explanation is that both human
426 population size and connectivity increase with island area as well as colonization pressure.
427 Thus, the effect of island area on alien diversities is masked by the effect of anthropogenic
428 variables (Blackburn et al. 2008; Moser et al. 2018), while area has a direct effect for native
429 diversities (Fig. S7). Our study sheds light on the importance of mediators to explain the
430 impact of biogeographic variables on alien diversities. Indeed, direct effects of biogeographic
431 drivers on birds FD, PD, SES-FD, and SES-PD were often non-significant, and their total
432 effects were related to indirect effects mediated by anthropogenic and biotic drivers.

433

434 **Limitations**
Although our study provided new insights on biological invasions on islands, there are limitations to be acknowledged. First, while the GAVIA database is the most comprehensive source for alien bird distributions worldwide, it is not regularly being updated, and for ten species known to have an established population on an oceanic island, the alien range map was not available. We were able to retrieve the colonization pressure only for 96 out of 407 islands, partly limiting our analyses using this variable. Yet, we could prove it was a critical factor for explaining alien taxonomic richness, but which did not have any direct effect on alien FD or PD (Supplementary text, Fig. S5). Second, SEM is usually designed for causal relationships. However, it is unlikely to precisely get the direct links between predictors at such a spatial scale, forcing us to deal with many latent variables. As such, model construction led to the inclusion of a correlated error between the human-related variables and the native biotic context, based on two a priori hypotheses: (i) expert-derived maps for calculating native richness tend to overestimate species presence on islands, scaling with human presence (Nori et al. 2022); (ii) islands with more resources and thus with a higher native richness are more attractive to humans, resulting in an increased human presence (Luck 2007).

451

## Conclusion

We found that humans provoked drastic changes in ecosystem compositions across all facets of diversity. Our study allowed us to identify the drivers of multiple facets of alien diversity as a first step towards anticipating the risk posed by biological invasions. We believe that examining new insular communities, thus rethinking the island biogeography in the Anthropocene, is of primary interest for forecasting the impacts of other global threats on islands, such as climate or land-use changes.
459 ACKNOWLEDGMENTS

460 Many thanks to Martin Philippe and James Grace for answering our questions on the methods.

461 We thank Ana Rodrigues, Wilfried Thuiller, and Lise Comte for discussing this project. CM

462 was supported by a PhD grant from the ENS-PSL and lately by the RIVAGE project funded

463 by the CESAB of the French Foundation for Research on Biodiversity (FRB). CB and JMJ

464 were funded by their salaries as French and German public servants, respectively.

465

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<table><caption>Table 1. Hypotheses on the factors driving alien bird diversities (i.e., SR: species richness; FD: functional richness; PD: phylogenetic richness)</caption><thead><tr><td>Response</td><td>Driver</td><td>Variable</td><td>Hypothesized relationship</td><td>Source</td></tr></thead><tbody><tr><td>Alien FD, PD</td><td>Alien taxonomic richness</td><td>Alien SR</td><td>(+) Alien FD and PD are partially dependent on alien SR</td><td>(Faith 1992; Mouchet et al. 2010)</td></tr><tr><td>Alien SES-FD, SES-PD</td><td>Alien taxonomic richness</td><td>Alien SR</td><td>(+/-) Depending on the assembly rules, species close to each other can be favored by habitat filtering or disfavored to limit competition</td><td>(Tilman 2004; Mouchet et al. 2010)</td></tr><tr><td>Alien SR, FD</td><td>Area</td><td>Area</td><td>(+) Species-area relationship applied to aliens (alien SR)<br>(+) FD-area relationship posits that FD will increase with area but will reach a plateau because of functional redundancy between species (alien FD)</td><td>(MacArthur & Wilson 1967; Case 1996; Blackburn et al. 2008, 2016)</td></tr><tr><td>Alien FD, PD</td><td>Elevation</td><td>Elevation</td><td>(+) Habitat heterogeneity promotes the establishment of species with distinct traits</td><td>(Case 1996; Walsh et al. 2012)</td></tr><tr><td>Alien SR</td><td>Latitude</td><td>Latitude</td><td>(+) Alien taxonomic richness higher toward temperate zones</td><td>(Dyer et al. 2020)</td></tr><tr><td>Alien SR</td><td>Isolation</td><td>Distance to continent; Surrounding landmass</td><td>(+) Isolated islands more prone to alien species introduction and establishment</td><td>(Moser et al. 2018)</td></tr><tr><td>Alien SR, FD, PD</td><td>Native biota</td><td>Native taxonomic richness; Native FD; Native PD</td><td>(-) Biotic resistance hypothesis<br>(+) Rich-get-richer hypothesis</td><td>(Levine & D'Antonio 1999; Stohlgren et al. 2006; Dyer et al. 2017)</td></tr><tr><td>Alien SR</td><td>Colonization pressure</td><td>Alien CP</td><td>(+) A high number of introduced species promotes a high number of established species</td><td>(Dyer et al. 2017a; Blackburn et al. 2020)</td></tr><tr><td>Alien SR, FD, PD</td><td>Human exchanges and intensity of presence</td><td>GDP; Population size; Human connectivity</td><td>(+) Colonization pressure increases with human exchanges which are driven by population density, tourism, island accessibility and wealth</td><td>(Dawson et al. 2017; Dyer et al. 2017a)</td></tr><tr><td>Alien SR, FD</td><td>Habitat modification</td><td>Static habitat modification; Change habitat modification</td><td>(+) Alien species thrive in disturbed habitats (alien SR)<br>(+) Disturbed habitats offer new niches and favor new species traits (alien FD)</td><td>(Sánchez-Ortiz et al. 2020)</td></tr></tbody></table>
<figure><img src="image_2.png" /><figcaption>**Figure 1.** Global association between functional and phylogenetic diversities of alien birds on oceanic islands. (A) Spatial variation of functional diversity (Alien FD, color of the rings) and phylogenetic diversity (Alien PD, size of the rings) of alien birds on the 407 islands. Values of alien FD (B) and alien PD (C) for islands within each region. Only regions with more than ten islands are shown.</figcaption></figure>
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**Figure 2.** Deviations of functional and phylogenetic diversities from taxonomic diversity on islands. Mean standardized effect sizes (SES) of functional and phylogenetic diversities across all islands separated by region. The points represent the mean SES-FD and SES-PD per region, and horizontal and vertical bars represent the standard deviation of SES-FD and SES-PD within each region, respectively. Only regions with more than ten islands are shown. Among the 407 islands, respectively 15 and 100 islands had SES-FD and SES-PD below -1.96, which is the threshold for assemblages being significantly more clustered than expected by chance. 3 islands had SES-PD above 1.96, meaning their alien assemblages were significantly more dispersed than expected by chance.
<figure><img src="image_4.png" /><figcaption>**Figure 3.** Direct, indirect, and total effects of all explanatory variables on (A) functional diversity (FD; and its associated SES) and (B) phylogenetic diversity (PD, and its associated SES) of alien birds. The zoogeographic region for birds of each island was integrated as a random effect in all relationships. Dots represent standardized mean effects, and error bars depict 95% confidence intervals (shaded colors represent intervals crossing zero). Variable names are colored following their context: biotic (green), human (blue), and biogeographical (orange).</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Figure 4. Schematic path diagram representing causal relationships between the geological, human, and biotic insular context and the alien functional diversity (FD, panel A) and phylogenetic diversity (PD; panel B). Line width is scaled to the absolute value of effects.</figcaption></figure>

Standardized R² coefficients are specified in brackets for each endogenous variable. Variable names are colored following their context: biotic (green), human (blue), and biogeographical (orange). We only represented the effects for variables with a significant total effect on FD or PD. Dashed lines represent variables with a significant total effect (resulting from adding direct and multiple indirect effects through other variables), but no direct or indirect significant effect. All links between endogenous variables are depicted in Fig. S7.