Traits and the City: functional trait space in urban bird and bat assemblages

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This study characterises the functional space of urban bird and bat assemblages in the city of Poitiers, France. Specifically, our objectives were to quantify functional diversity across Urban Heat and Cool Islands, test the role of rare species, identify traits linked to urban tolerance or sensitivity, and examine whether birds and bats share ecological strategies in response to urban stressors. Bird and bat assemblages were sampled across UHIs and UCIs within Poitiers. Functional traits were compiled for each species, and relationships with fine-scale urban landscape variables were assessed using fourth-corner analysis. We quantified functional diversity metrics (alpha, rarity, beta) and trait distributions using Community Weighted Means. Birds and bats exhibited contrasting functional responses to urbanisation. In birds, functional alpha-diversity was higher in UHIs than in UCIs, driven mainly by functional rarity rather than local habitat variables. In contrast, bat functional diversity decreased in UHIs, with no detectable contribution of rare species but a strong influence of urban landscape structure. Urban tolerance was associated with high dispersal and longevity in birds, and with larger size and clutter-adapted echolocation in bats. Both groups shared key ecological adaptations to urbanisation which likely enables persistence in densely urbanised environments. Overall, urbanisation acts as a strong ecological filter, but its influence differs across taxa. This study confirms once again that functional approaches reveal hidden information in taxonomic-only approaches which reveal essential information for urban landscape managing and conservation. urbanisation birds bats functional diversity functional rarity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Human population is growing at an exponential rate (United Nations 2019), leading to profound and often irreversible changes in global land use, as natural habitats are increasingly replaced by human infrastructure (Li et al. 2025 ; United Nations & Department of Economic and Social Affairs 2019). Urbanisation is recognised as a major contributor to global biodiversity declines (Piano et al. 2017 ), often illustrated by the fact that only a subset of species can withstand such disturbances (Sol et al. 2017 ). Understanding which species traits or environmental conditions enable some taxa to persist in, or exclude others from, urban ecosystems is, therefore, essential. Urbanisation affects biodiversity in different ways across taxa. Some studies report increased abundance or richness at intermediate or high urban levels (Kondratyeva et al. 2020 ), whereas others show marked declines in species diversity and abundance (Sol et al. 2014 ). These contrasting patterns suggest that the effects of urban development on species assemblages are highly context-dependent, where “context” refers to both the taxon considered and the specific landscape or urban characteristics. However, certain functional traits or ecological functions may persist, or even be favoured, in highly urbanised environments, facilitating the colonisation of urban ecosystems (Brown & Graham 2015 ). The exploration of functional diversity allows us to evaluate ecosystem functions and processes through species’ functional traits (Sol et al. 2020 ). Indeed, trait diversity strongly influences ecosystem functions in multiple ways (Cardinale et al. 2013 ). Generally, highly urbanised areas, experience declines in functional diversity due to a reduction in species with high trait divergence, making assemblages more homogeneous and, thus, less resilient to disturbances (Johnson & Munshi-South 2017 ). At the same time, rare or low-abundance species have been recognised as crucial for maintaining functional diversity in ecosystems in some cases, as their distinctive traits can make outsized contributions to ecosystem services, and resilience (Leitão et al. 2016 ; Lin et al. 2024 ; Zabala-Forero et al. 2025 ). Yet the drivers of functional diversity in cities are complex and asymmetric, calling for further research to clarify these patterns and guide urban planning and conservation. Birds and bats, as the sole flying vertebrates in temperate ecosystems, have successfully colonised urban environments (Guetté et al. 2017 ; Mimet et al. 2020 ). Birds’ ability to colonise cities depends on a specific combination of morphological traits, foraging and habitat breadth, geographical range size, nesting behaviour, and reproductive success (Kark et al. 2007 ; Sol et al. 2014 ). Along increasing gradients of urbanisation intensity, some studies have reported reductions in the functional diversity of bird assemblages (Aronson et al. 2020; Sol et al. 2020 ), whereas others have shown that urban areas can retain substantial levels of avian functional diversity (Oliveira Hagen et al. 2017 ; Querejeta et al. 2025 ). “Urban winner” species are often characterised by generalist traits, which mainly represented by members of the Passeridae, Columbidae, Corvidae, and Sturnidae families (Guetté et al. 2017 ; Sol et al. 2014 ). Certain functional traits may enable birds to respond adaptively to urban stressors, although behavioural plasticity has been less strongly associated with urban tolerance than previously thought (Guetté et al. 2017 ; Sol et al. 2014 ). Such advantageous traits are typically linked to generalist resource use, while migratory species and those that nest in shrubs or on the ground are more closely associated with non-urban, natural forest habitats (Buron et al. 2022 ; Neate-Clegg et al. 2023 ). In the case of bats, a highly phylogenetically diverse group (Teeling et al. 2005 ), their functional responses to urban stressors have been shown to be species-specific (Ancillotto et al. 2019 ; Jung & Threlfall 2016 ; Russo & Ancillotto 2015 ), with certain species possessing specific functional traits that make them less vulnerable to urban landscapes than others (Avila-Flores & Fenton 2005 ; Jung & Threlfall 2018 ). Despite this high variability, urban-tolerant bat species tend to share a set of traits. In general, urban bats fly faster (Avila-Flores & Fenton 2005 ), though with less agility (Ancillotto et al. 2015 ; Egert-Berg et al. 2021 ; Jung & Threlfall, 2016 ) and produce lower-frequency echolocation calls (Threlfall et al. 2011). Regarding feeding behaviour, species that forage in open or edge spaces and exhibit flexible roosting strategies (Jung & Threlfall 2018 ), such as using human-associated structures like caves, tunnels, or abandoned buildings (Briones-Salas et al. 2024 ), are also more successful in urban environments. Despite being the most conspicuous urban assemblages, birds and bats have rarely been studied together in urban environments (Jung & Threlfall 2016 ; Querejeta et al. 2025 ; Tiago et al. 2024 ). To address this gap, we surveyed birds’ and bats’ assemblages to explore their functional space. Specifically, we examined the effect of Urban Heat Islands (UHIs) and Urban Cool Islands (UCIs) on urban bird and bat assemblages in the medium-size city of Poitiers, France. UHIs can be defined as areas within the cities, which are experiencing a rise of temperatures, mainly due to highly dense urbanisation, human activities and land modification. On contrast, UCIs are urban sites represented by less rise of temperature in comparison to UHIs, due to a lighter form of urbanisation (Jame et al., 2024 ). Using UHIs as a proxy for highly urbanised areas, Querejeta et al. ( 2025 ) analysed the taxonomic, phylogenetic, and functional diversity of birds and bats in the study area of Poitiers, France, using the same field sampling and biodiversity dataset as the present study. Results showed that bat taxonomic, phylogenetic, and functional diversity decline within UHIs and along an artificialisation gradient, while in birds only taxonomic diversity declines, with phylogenetic diversity unchanged and functional diversity even higher in UHIs. In this context, this study aims to address the following specific objectives: (1) determine the differences between UHIs and UCIs (as a proxy for contrasting urban microclimates), as well as along an artificialisation gradient in functional diversity and redundancy (2) to examine whether rare species drive functional diversity within the urban ecosystem; (3) to uncover functional traits that confer either tolerance or sensitivity to extreme urbanisation and its associated microclimatic effects; and (4) to identify shared functional traits or ecological strategies, in order to determine whether specific traits are similarly favoured or filtered out in both urban bird and bat assemblages. As bats have been reported to be more vulnerable to dense urbanisation(Aronson et al. 2014 ; Jung et al. 2018), we hypothesized that the functional response would differ between bird and bat urban assemblages, with distinct functional traits conferring tolerance to urban stressors. Moreover, we hypothesized that functionally rare species (Basile 2022 ; Leitão et al. 2016 ) would drive functional diversity in both urban bird communities, while the effect of landscape variables and dominant or abundant species would be the most important driver in the case of bats (Cisneros et al., 2016 ). 2. Material and Methods 2.1. Study area and design The spatial distribution of UHIs and UCIs was determined using high-resolution mapping based primarily on Land Surface Temperature (LST) and the Heat Mitigation Index (HMI) (Jame et al., 2024 ). Then, urban bird and bat communities were sampled at 25 UHIs and 25 UCIs previously identified in Poitiers, France. The abundance of birds was surveyed following the French EPOC protocol (Fontaine et al., 2020) during two periods in spring 2023 (April and June), with species identified by song or sight and breeding status recorded. The frequency of bats was sampled acoustically between June and August 2023 using TeensyRecorders deployed for three nights per site, with one standardised night retained per point. Sonograms were processed with the software Kaleidoscope and verified manually (Barataud M., 2020 ). While samples are broadly identical (i.e. located in UHIs and UCIs) for both assemblages, bat sampling sites have been shifted from bird sampling locations in certain geographical points, as bat acoustic recorders must be place in safe and fresh places. A spatial autocorrelation analysis employing the Procrustes method was conducted to assess whether differences in the composition of bird and bat assemblages were related to the geographic distances among urban site types, implemented via the protest function in the vegan R package (Oksanen et al., 2013 ). Data has been deposited in figshare https://figshare.com/s/ee685a6c019f2024513a.2.2 . Landscape urban variables Landscape environmental variables were estimated separately for birds and bats within a 200 m buffer around each sampling location. This scale is relevant to birds, bats, and their prey. On one hand, we used a high-resolution land cover map ( i.e. 1 m resolution) to extract vegetation structure (including tree cover and strata diversity), built environment density, and distances to rural and aquatic. To assess the differences in landscape heterogeneity between sampling sites located in UHIs and UCIs, we performed a multivariate dispersion analysis on a Euclidean distance matrix followed by a permutational test (999 iterations) using vegan R package, respectively (Oksanen et al. 2013 ). To evaluate how sensitive our results were to sample size, we implemented a custom sensitivity analysis that repeatedly subsamples the dataset and re-runs the multivariate dispersion analysis (200 iterations with 999 permutations each) using the packages vegan (Oksanen et al. 2013 ) and dplyr (Wickham et al. 2021 ).All analyses were performed in R (R Core Team 2025). 2.3. Fourth-corner analysis To explore how species’ functional traits mediate their response to urban landscape variables, we applied a fourth-corner analysis using the mvabund R package (Wang et al. 2017 ). To simplify the analysis, we retained only those urban landscape variables that were significantly correlated with functional diversity, as assessed using the ggpubr R package (Kassambara 2020) (Supporting Information B, Table S1 ): density of building infrastructures, of impervious surfaces, of overall vegetation, of tree vegetation, distance to natural and semi-natural areas and to permanent and temporal wetlands. To include categorical traits in the analysis, we converted them into binary (dummy) variables. We selected the strongest trait-environment interactions by fitting the model using a LASSO-penalized regression. However, because the LASSO approach does not provide formal significance tests, we then re-fitted the model without the penalty to assess the statistical significance of the associations using a permutation-based ANOVA. 2.4. Landscape Principal Component Analysis (PCA) To reduce dimensionality and summarise environmental variables, we performed a Principal Component Analysis (PCA) in which the first axis (PC1) represented the landscape composition or “Rate of Artificialisation”, and the second axis (PC2) reflected the “Landscape Configuration” or PC2. In both assemblages, PC1 is mainly driven by density of vegetation, tree vegetation, impervious surfaces and buildings while PC2 is driven mainly by diversity of vegetation strata and distance to permanent wetlands. All subsequent analyses on urban landscape have been done using urban PCA components, PC1 and PC2. 2.6. Bird and bat functional traits and alpha-diversity metrics We used bird and bat functional traits, which could potentially be associated with responses to urbanisation, to compute functional alpha-diversity metrics. In the case of birds, 14 functional traits were used, nine quantitative and five nominal, whereas for bats, 12 functional traits were compiled, of which eight are quantitative and four nominal (Table 1 ). Detailed information about bird and bat functional traits can be found in Supporting Information B, Table S2 . Table 1 Summary table of functional traits used in this study for urban birds’ and bats’ assemblages. Categorical traits are collapsed in one type of category. Trait category Trait type Bird traits Bat traits Morphological Quantitative Beak length, tarsus length, Hand-Wing index (HWI), body mass Forearm length, body mass Life-history Quantitative Clutch size, lifespan Lifespan Habitat-related Quantitative Species Specialisation Index (SSI), Species Temperature Index (STI) Species Specialisation Index (SSI), Species Temperature Index (STI) Echolocation Quantitative — Call duration, call peak frequency Geographic Quantitative Geographic range size Geographic range size Diverse categories Categorical Habitat type, migratory behaviour, main lifestyle, trophic level, feeding niche Call type, primary hibernation roost, main maternity roost, main prey type To quantify functional alpha-diversity, we computed pairwise species distances using the Gower method based on functional traits (Magneville et al. 2022 ). These distances, combined with species abundance (birds) or frequency (bats), were used to construct the functional space via Principal Coordinates Analysis (PCoA). Functional Richness (FRic) and Mean Functional Distance (MFD), representing respectively the occupied trait space and mean functional dissimilarity among species (Villéger et al. 2008; Kembel et al. 2010 ), were computed using mFD R package (Magneville et al. 2022 ). Standardised effect sizes were derived from null models, except for MFD. Functional Redundancy (FRed) was defined as 1 – (FRic/species richness), indicating the extent of overlap in functional roles. To assess the functional rarity of urban bird and bat local assemblages, we computed functional distinctiveness and scarcity for each species using the funrar R package (Violle et al. 2017 ). These metrics were calculated based on a Gower distance matrix of species traits (as described above). Functional Distinctiveness (FDi) quantifies how functionally different a species is from the other species in the same community, with values ranging from 0 (not functionally distinct) to 1 (highly distinct). Functional Scarcity (FSi) measures how locally rare a species is relative to the other species in the community, based on its relative abundance, also ranging from 0 (locally abundant) to 1 (highly scarce). Furthermore, we identified the top 10% most distinctive and most scarce species within each assemblage and recalculated all functional alpha-diversity metrics after simulating the loss of these species. We then used the Kruskal–Wallis test followed by Dunn’s post hoc test, via FSA R package (Dinno & Dinno 2017 ), to assess whether the loss of these rare species significantly affected functional diversity. Finally, we calculated the percentage contribution of these species to the functional alpha-diversity metrics that were significantly affected by the loss of distinctive and/or scarce species. These analyses were performed using a customized R script, leveraging the dplyr and tidyr R packages (Wickham et al. 2019 , 2021 ). Generalized Linear Models (GLMs) were fitted to assess whether functional alpha diversity and rarity metrics were primarily influenced by the type of urban site (UHI or UCI), the urban PCA components, PC1 and PC2. Models were built using the glm function from the base R stats package, with functional alpha-diversity and rarity metrics as dependent variables, and urban PCA components as fixed effects. Model selection was based on the corrected Akaike Information Criterion (AICc), using the dredge and select.models functions from the MuMIn package (Barton & Barton 2015 ). All dependent variables were modelled assuming a Gaussian distribution with an identity link function. Model diagnostics, including checks for overdispersion, outliers, and zero-inflation, were performed using the DHARMa package (Hartig 2022 ). All analyses were performed using R version 4.4.1 (R Core Team 2024 ). 2.7. Bird and bat functional beta-diversity To assess functional beta-diversity among bird and bat communities, we used a distance-based Redundancy Analysis (dbRDA) based on Bray–Curtis distances, implemented via the vegan R package (Oksanen et al. 2013 ). 2.8. Community Weighted Means of functional traits To evaluate whether certain functional traits were conserved within UHIs or urban cool islands (UCIs) in bird and bat assemblages, we calculated community-weighted means (CWMs) for each quantitative trait using dplyr R package (Wickham et al. 2021 ). For birds, these included indices describing temperature and habitat specialization, body mass, morphological dimensions (beak, tarsus, and Hand-Wing Index), reproductive traits (egg number and lifespan), and geographic range. For bats, we computed CWMs for temperature and habitat specialisation, body mass, forearm length, geographic range, lifespan, and echolocation characteristics (call duration and peak frequency). 2.9. Correlations and effects of the type of urban point and urban landscape variables on CWMs of functional traits Pearson gradient correlations were also performed between the community-weighted means of quantitative functional traits and the landscape principal components: “Rate of Artificialisation” (PC1) and “Landscape Configuration” (PC2). We computed correlations and displayed them as scatterplots using the ggpubr package in R (Kassambara 2023 ). Moreover, we repeated the Generalized Linear Model (GLM) analyses described above (section 2.6 ), using CWMs of functional traits as dependent variables, with the type of urban point, UHI or UCI, and urban PCA components as fixed effects. 3. Results 3.1. Differences in landscape heterogeneity and functional trait space between UHIs and UCIs The lack of significance in the Procrustes analyses suggests that spatial proximity did not influence the observed differences in bird (Protest R = 0.26, p = 0.74) and bat (Protest R = 0.19, p = 0.843) community composition, indicating an absence of spatial autocorrelation. According to the multivariate dispersion analysis based on urban landscape variables and sampling locations of urban bird assemblages, landscape heterogeneity was significantly higher in sampling sites located in UHIs than those in UCIs (F = 14.768, prand < 0.001). For bats, heterogeneity was also higher in UHIs, but the difference was not statistically significant compared to UCIs (F = 3.1466, prand = 0.088). Regarding the sensitivity analysis, the lack of significant differences in landscape heterogeneity between UHIs and UCIs for bats appears to be due to small sample size, as our simulations indicated that significance would be reached with at least 65 urban points, whereas for birds it would be reached with 45. The exploration to beta-diversity, through dbRDA ordination (Fig. 1 ), revealed bird functional space within UHIs wider than within UCIs. 3.2. Effect of urban landscape variables in bird and bat functional traits Bird species traits did not significantly influence their distribution in line with urban landscape variables (likelihood ratio: deviance = 717.7, P = 0.091). In contrast, bat species’ traits influenced their distribution according to urban landscape variables (likelihood ratio: deviance = 275.8, P = 0.001) (Fig. 2 ). The fourth-corner analysis revealed a negative association between the presence of underground maternity roosts and the distance to natural and semi-natural areas, as well as between having Hemiptera as the main prey and the distance to permanent water bodies. Conversely, a strong positive association was found between vegetation cover density and having Lepidoptera as the main prey. Regarding echolocation traits, call duration was negatively associated with vegetation cover density (Fig. 2 ). 3.3. Effect of urbanisation on functional alpha-diversity Regarding functional alpha-diversity, Functional Richness (FRic) was greater in UCIs than in UHIs for both birds and bats. In contrast, Mean Functional Distance (MFD) was higher in UHIs for bats, although this difference was significant between urban site types only when using the standardised measure (Supporting Information A, Fig. S1 ), whereas birds showed the opposite pattern. Functional Redundancy (FRed) was higher in UHIs for both urban assemblages (Fig. 3 & Supporting Information A, Fig. S2 ). As the standardised effect sizes of all functional alpha-diversity metrics mirrored the patterns of the observed values, we focus hereafter on the observed metrics. The only exception is bat MFD, which showed no significant effect in the observed data, but whose SES revealed a significant effect of the type of urban point, with higher values in UHIs than in UCIs (estimate = 0.8229 ± 0.2105, t = 3.91, p = 2.91 × 10⁻⁴) (Fig. 3 & Supporting Information A, Fig. S1 ), which showed the same pattern but significant (Supporting Information A, Fig. S2 ). For birds, FRic was significantly negatively correlated with the “Rate of Artificialisation” (PC1) while MFD displayed significant positive correlations. FRed in birds showed also a significant positive correlation. For bats, FRic was significantly negatively correlated with PC1, while MFD a negative but non-significant correlation. However, its standardised effect size was shown to be significantly negative (Supporting Information A, Fig. S2 ). Bat’s FRed was significantly positively correlated. Regarding “Landscape Configuration” (PC2), the only significant relationship detected was a positive correlation with bird FRic. (Fig. 4 ; Supporting Information A, Fig.S3). According to the GLM results (Supporting Information B, Table S3A), birds’ FRed were influenced by the type of urban site, whereas FRic was associated with PC2 and MFD with PC1. In the case of bats, functional alpha-diversity metrics were only influenced by the type of urban point (UHI or UCI), rather than by PC1 or PC2. 3.4. Contribution of functional rarity to bird and bat urban functional diversity In the case of correlations with functional rarity metrics, Functional Distinctiveness (FDi) showed a significant, positive and important correlation with PC1 for birds (R = 0.33). In the case of bats, the correlation was significant, negative and moderate (R = -0.17). (Fig. 5 ). In line, FDi showed significant differences between UHIs and UCIs in bats but not for birds (Fig. 4 ). The Functional Scarcity (FSi) of birds and bats showed a positive and significant correlation with PC1 but with a weak signal (R < 0.1) (Fig. 5 ) and did not differ between UHIs and UCIs (Fig. 4 ) (Supporting Information B, Table S3A). Besides, concerning PC2, all correlations were significant but not important (not shown). Further details about FDi and FSi of each of the species forming urban assemblages is available at Supporting Information B, Table S4. According to Kruskal–Wallis and Dunn tests, in birds, the loss of the 10% most distinctive species significantly affected FRic, MFD, and FRed, whereas the loss of the 10% scarcest species significantly impacted only MFD. In contrast, for bats, the loss of either the most distinctive or the scarcest species had no significant effect on any functional diversity metric (Fig. 5 , Fig. 6 & Supporting Information B, Table S5). 3.5. Bird and bat urban functional traits between UHIs and UCIs and along an artificialisation gradient According to CWMs, birds’ functional composition varied mainly with PC1, with communities in more urbanised areas dominated by species with longer wings, greater longevity, wider ranges, and higher temperature affinities. Tarsus length decreased with increasing PC2 and was also influenced by the type of urban point (Supporting Information A, Fig. S5A; Supporting Information B, Table S3B). For bats, call duration increased and peak frequency decreased along PC1, reflecting acoustic adaptations to urban clutter and noise. Traits associated with temperature tolerance and ecological specialisation increased with PC2, indicating that more connected urban landscapes supported thermophilic and specialised species (Supporting Information A, Fig. S5B; Supporting Information B, Table S3B). For birds, species associated with forests were more abundant in UCIs, whereas those adapted to human-modified habitats prevailed in UHIs. Herbivores and granivores were slightly more abundant in UHIs, while carnivores and invertivores dominated UCIs. Terrestrial species were more common in UHIs, and insessorial species in UCIs. Differences in migratory status were limited (Supporting Information A, Fig. S6A). For bats, FM/QCF call types and Diptera prey dominated both UHIs and UCIs, though Coleoptera were more frequent in UHIs. Tree roosts prevailed overall, with rock crevices more typical of UHIs. Maternity roosts were mainly in human-made structures, followed by tree roosts across both site types (Supporting Information A, Fig. S6B). 4. Discussion Our study further confirms that functional traits are powerful tools for understanding how species respond to environmental factors, including urban stressors (Petchey & Gaston 2002 ). Our results support the hypothesis that, although birds and bats are both flying vertebrates, their functional responses to urbanisation differ, while some strategies remain conserved within urban heat islands in both groups. 4.1. Different functional responses of urban bird and bat assemblages to strong artificialisation Although highly urbanised sites, such as UHIs, exhibited higher Mean Functional Distance (MFD) in bird assemblages, this was not accompanied by increased Functional Richness (FRic). This incongruence is not surprising. Abundance-weighted metrics such as MFD are not linearly related to species richness, while trait-space volume metrics like FRic almost always are (de Bello et al. 2016 ). These peculiarities help us understand why functional diversity appeared higher in highly urbanised sites, as UHIs, than in UCIs. Such patterns may be linked to the composition of urban bird assemblages. In our case, Poitiers’ urban bird community is dominated mainly by Passeriformes, leading to low evolutionary distinctiveness (Querejeta et al. 2025 ). In fact, closely related communities have shown to have high trait divergence in several cases, potentially due to ecological opportunity and rapid trait divergence (Losos 2008 ; Oliveira Hagen et al. 2017 ). This divergence is, indeed, reflected in the functional space, through dbRDA ordination, where UHIs showed a broader ellipse than UCIs, highlighting greater variation in trait composition across sites. Our results echo findings from other studies (Lee et al. 2021 ; Oliveira Hagen et al. 2017 ). For instance, Oliveira-Hagen et al. (2017) reported higher avian functional diversity in urban areas than in nearby rural sites, even after controlling for species richness. They attributed this “paradox” to the habitat heterogeneity offered by urban environments compared to more homogeneous rural landscapes. A similar process seems to operate in our study area: UHIs are more heterogeneous than UCIs. This heterogeneity likely contributes to the higher functional diversity we observed. However, this may be only part of they as our non-significant fourth-corner analysis shows that bird traits’ distribution is not entirely shaped by urban landscape variables. This suggests that other processes may also be at play. One possibility is the role of distinctive or functionally rare bird species, which appear to increase along the urbanisation gradient. These species may be a key driver of functional diversity in birds, unlike in bats, where such a pattern was not detected. Concerning bird functional rarity, we can confirm our initial hypothesis as our results indicate that the disappearance of distinctive species would strongly affect functional diversity. This pattern is consistent with previous work showing that rare bird species often contribute disproportionately to the functional structure of assemblages (Leitão et al. 2016 ). Their loss could, thus, have cascaded consequences and ultimately compromising the long-term provision of ecosystem services. In our study, the distinctive species grey heron ( Ardea cinerea ) illustrates this point well. As the sole representative of the order Pelecaniformes and one of the few aquatic predators specialised in wetland habitats, it maintains a high share of functional diversity despite its rarity. By contrast, bat assemblages do not exhibit the same pattern as the disappearance of functionally distinctive species appears to have little effect on overall functional diversity. In contrast, functional diversity appears to be shaped mostly by the collective contribution of all species, or by the dominance of abundant generalists such as the common pipistrelle, as we had initially hypothesized. This interpretation is supported by our fourth-corner analysis, which shows that bat functional assemblages in urban areas are strongly structured by landscape variables. Taken together, these results suggest that bats are directly affected by anthropogenic stressors and may, therefore, be more vulnerable to intense urbanisation than birds. Indeed, bird functional diversity is strongly influenced by rare species, which serves as a reminder that their disappearance could have disproportionate impacts on entire assemblages. Bird and bat Functional Redundancy (FRed) increased in highly urbanised sites (UHIs) compared to UCIs. This finding aligns with the idea that urbanisation reduces trait diversity and promotes functional homogenisation, whereby several species fulfil similar functional roles (Palacio et al. 2018 ). In our study, this is illustrated by the dominance of generalist traits, such as granivores, which tend to replace more specialised traits, such as insectivores, thereby increasing FRed within UHIs. Generalists can be considered redundant due to their high niche overlap (Palacio et al. 2018 ). While FRed may buffer ecosystems against species loss in the short term, it can also reduce ecosystem resilience in the long term by diminishing functional complementarity. Indeed, some urban bird assemblages have already lost nectivorous pollinators, indicating low FRed for that particular ecological role (Pauw & Louw 2012 ). However, urban areas will never host as many species as natural habitats due to intense human pressures such as buildings, roads, and constant human activity. Moreover, the limited number of microhabitats available within cities constrains the range of ecological niches. Therefore, maintaining both high FRed and substantial MFD in urban bird communities is essential for promoting ecosystem resilience. FRed ensures that key ecological roles are preserved even if some species decline, whereas a high MFD enables communities to retain a broad array of ecological strategies, allowing them to cope with environmental changes and to exploit the full range of available urban habitats. Indeed, in our bird assemblages, we observed that high functional diversity, as measured by MFD, co-occurs with substantial FRed. Indeed, it has been argued that FRed and diversity are not mutually exclusive, as species may be functionally similar in some effect traits while remaining distinct in response traits, thereby maintaining both ecological insurance and niche differentiation (Fischer & de Bello 2023 ). Similarly, communities may be able to retain high functional diversity together with redundancy across environmental gradients, suggesting that environmental heterogeneity promotes multiple coexisting strategies that enhance ecosystem resilience (Monge-González et al. 2021 ). Indeed, in our study, UHIs exhibited higher landscape heterogeneity. Overall, our study reveals a complex pattern of both congruence and divergence in bird and bat functional diversity metrics along the urbanisation gradient. 4.2. Urban landscape variables influence bat but not bird functional traits Our study found no significant associations between urban landscape variables and bird functional traits based on the fourth-corner analysis. This suggests that other factors, such as the presence and influence of functionally rare species, may be driving the observed patterns in urban functional structure. This finding also aligns with a potential environmental filtering process that has already shaped bird colonization before reaching the urban core (Querejeta et al. 2025 ; Sol et al. 2014 ). In other words, the effect of landscape variables likely occurs along the rural-to-urban gradient, rather than between UCIs and UHIs. In contrast, bat functional traits showed significant associations with urban landscape variables, indicating an ongoing process of functional filtering along the urbanisation gradient, from UCIs to UHIs driven by the higher sensitivity to urban stressors. Among the associations detected, bat species were found to rely more on human-made structures and less on underground locations for roosting as the distance from natural and semi-natural areas increased. This pattern supports the idea that species with greater flexibility in roost-site selection are more successful colonisers of urban environments (Jung & Threlfall 2018 ), highlighting the importance of maintaining and restoring natural roosting and maternity sites to enhance bat species and functional diversity in cities. The strongest positive association between landscape and functional traits was observed in bat species that primarily feed on Lepidoptera, which were positively correlated with the density of vegetation cover. Indeed, urban moth communities are highly sensitive to vegetation structure, making this finding ecologically meaningful (Tyler 2020 hätalo et al. 2024 ). In our study, key Lepidoptera-feeding bats, including species from the genera Rhinolophus , Plecotus , Barbastella , and Myotis , were predominantly found in UCIs rather than in UHIs. This suggests that the availability of Lepidoptera, and feeding resources in general, may act as a limiting factor for these species in urban settings. Accordingly, we recommend the implementation of urban green infrastructure that prioritizes native plant species, high-quality natural habitats, and ecological connectivity with surrounding rural and natural areas to promote ecological continuity. 4.3. Certain birds and bats functional traits are conserved within UHIs Overall, our study has revealed that bird and bat colonisation of highly dense anthropised sites is represented by favouring certain traits over others within UHIs. In the case of birds, Community Weighted Means of Hand-Wing Index or HWI, geographical distribution range, lifespan, Community Specialization Index or CSI and Community Temperature Index or CTI are explained by the PC1, as they all increase exponentially along a gradient with higher values of urbanisation. Birds with higher HWI, indicating more pointed wings and greater dispersal ability, were more conserved in UHIs. This aligns with the idea that strong dispersers tend to have larger geographic ranges and are better equipped to colonise novel or disturbed environments, such as urban areas (Arango et al. 2022 ; Claramunt et al. 2022 ; Neate-Clegg et al. 2023 ). In addition to HWI, species with broad distribution ranges appear to also thrive in the highly urbanised landscape, suggesting that dispersal ability plays a key role in successful urban colonisation. Indeed, bird species found in European urban areas have been shown to exhibit greater dispersal abilities compared to those in more natural habitats (Møller 2009 ). Thus, dispersal abilities would enable birds, located in UHI to cover large areas and therefore seek resources in sites that are less hostile or competitive than UHI. An alternative explanation is that the observed variation in HWI may arise from differences in foraging modes, including flycatching and aerial insectivory, rather than from dispersal ability per se (Neate-Clegg et al. 2023 ). Moreover, the increase in lifespan associated with artificialisation may be related to a decrease in predation pressure at highly artificial sites (Eötvös et al. 2018 ), where birds may have chosen a strategy of living longer in order to learn to exploit urban environments (Neate-Clegg et al. 2023 ). Urban areas are warmer than their surroundings because built surfaces absorb and release heat (Aram et al. 2019 ). This effect peaks in dense zones such as UHIs. Accordingly, the rise in CTI with urbanisation reflects increasing thermal stress, with thermophilic species dominating the most modified environments (Barnagaud et al. 2012 ; Piano et al. 2017 ). At the same time, CWM of tarsus length is higher in UCIs, when comparing to UHIs, and decreases with higher values of PC2. Indeed, birds’ tarsus lengths are associated with locomotory performance, escape flight ability and, thus, capacity to avoid predators (Amiot et al. 2022 ). One hypothesis would lead us to expect a higher number of predators in less urbanised areas and, thus, more predation pressure (Eötvös et al. 2018 ). Therefore, this take-off capacity would lead birds to higher changes of survival within UCIs. However, the smaller tarsus lengths observed in urban passerines, the so-called “urban winners”, have been linked to the production of lower-quality offspring. This is concerning, as in species such as sparrows, the final tarsus length is typically attained at fledging (Gosler et al. 1998 ). This supports a second hypothesis, that increased urbanisation may reduce offspring quality in highly anthropised sites, potentially triggering a long-term degradation of urban bird communities and increasing the risk of local extinctions. Nonetheless, further observational and experimental research is needed to determine which mechanisms are driving these patterns. In relation to bat morphological traits, CWMs of forearm length and body mass were higher within UHIs and their variation was explained by the type of urban point, UHI and UCI. Longer forearm lengths are known to be closely associated to faster flight in open areas (Wood & Cousins 2023 ) and, potentially, more dispersal capacity, capacity which was also conserved in more urbanised sites in the case of birds. Indeed, a recent study has shown that certain UK urban bat assemblages were larger than in rural areas, potentially due to the absence of pesticides increasing insect availability (Hughes et al. 2024 ). In line with this, higher body mass may also lead to faster flight speed and larger flights which would make foraging activities more efficient (Jung & Threlfall 2018 ), and potentially in areas further from urban stressors. In fact, some light-tolerant bat species, such as the common pipistrelle ( Pipistrellus pipistrellus ) and the common noctule ( Nyctalus noctula ), are known to forage under city lights while maintaining their roosting sites in rural areas outside towns (Hale et al. 2012 ; Mathews et al. 2015 ). At the same time, echolocation is a defining trait in bats, shaping how they perceive and interact with their surroundings (Denzinger & Schnitzler 2013 ). Our results highlight call peak frequency and duration as key traits influencing adaptation to highly urbanised sites. Longer calls and lower peak frequencies increased with artificialisation, consistent with studies showing that such signals perform better in noisy, open urban environments (Avila-Flores & Fenton 2005 ; Jung & Threlfall 2018 ; Wolf et al. 2022 ). Lower frequencies reduce masking by high-frequency noise, while longer calls enhance spatial resolution (Bunkley et al. 2015 ; Hage et al. 2013 ). Conversely, according to fourth-corner results, call durations shortened with denser vegetation, supporting evidence that acoustic clutter promotes shorter, broadband calls (Suarez-Rubio et al. 2018 ; Starik & Göttert 2022 ). Undoubtedly, in strongly urbanised areas such as UHIs, morphological, echolocation, ecological, and thermal traits that increase the fitness and survival of birds and bats are consistently favoured. Yet, whether these traits are also different in surrounding rural areas requires further exploration of rural, peri-urban and urban assemblages. In the case of bats, shifts of activity, especially related to hunting behaviour would help shedding light onto the distribution of functional traits due to human modification. Overall, we have found not only dissimilarities but also similarities on the functional traits, which confer tolerance and/or vulnerability in birds and bats to urban environments. This leads us to reject our hypothesis in which functional traits that are associated with the colonisation of UHIs and UCIs were different between birds and bats. While the effect on some functional traits is specific from birds, such as more longevity and bigger distribution ranges in strong urbanised sites, and to bats, such as echolocation calls characteristics, several functional characteristics follow the same patterns in both groups. Indeed, higher dispersal capacities in highly dense urbanised sites related with bigger wings, as measured by HWI in birds and forearm lengths in bats is a common advantageous trait to colonize highly urbanised sites. It is, hence, plausible that only bird and bat species with high dispersal capacity can reach and persist in anthropised environments, migrating from rural roosts into cities where competition may be lower due to environmental filtering. However, longer wings because of longer forearms may be associated with a different diet more than to a real adaptation to urban environments. Moreover, higher specialisation and higher thermal tolerance associated with UHIs is another common characteristic related to habitat requirements. In fact, the higher specialization may be associated with higher landscape heterogeneity found in UHIs in comparison to UCIs. Despite species-specific traits, our analyses reveal that community composition along the urbanisation gradient is driven by the filtering of conserved functional traits that shape bird and bat distributions across UHIs and UCIs. 4.4.Towards multifunctional urban landscapes for conservation Conservation assessments based solely on assemblage composition or taxonomic diversity risk missing key ecological processes and can therefore lead to suboptimal conservation and urban management decisions (Laureto et al. 2015 ). Indeed, our functional approach has revealed key findings that may help enhance biodiversity in urban areas. For instance, our results suggest that bird assemblages are partly structured by functionally rare species, and that their local disappearance would disproportionately erode functional diversity. This implies that conservation efforts for urban birds should explicitly prioritise these functionally rare ‘outliers’ (Violle et al. 2017 ). In our case, this is mainly represented by aquatic predators such as the grey heron, whose distinctive traits and low redundancy make them irreplaceable contributors to ecosystem functioning. Aquatic avian predators are widely known to be scarce in urban environments. Similar patterns have been reported for fish-eating waterbirds in the highly urbanised New York/New Jersey Harbour, where suitable wetland habitats are limited. In that case, a dedicated conservation programme protects nesting islands and associated wetlands, couples habitat restoration with disturbance management, and relies on long-term monitoring to safeguard these top predators within a densely urbanised landscape (Craig et al. 2015 ). Ultimately, urban conservation strategies should aim to maintain the ecological functions carried by these trait outliers, notably through wetland protection, improved river habitat connectivity, and targeted management of vulnerable aquatic predator populations. At the same time, our study has shown low abundance of insectivorous birds compared to granivorous within the study area. Indeed, previous studies have shown that enhancing tree diversity and vegetation complexity in urban green spaces can increase insectivory by birds (Schillé et al. 2025). This measure could also be beneficial to increase the diversity of Lepidoptera-feeding bats in UHIs as insectivorous bats are known to respond positively to structurally complex vegetation and abundant insects near water bodies (Suarez-Rubio et al. 2018 ; Straka et al. 2020 ). Moreover, promoting high-quality insect communities within urban green-blue infrastructures has been identified as a key measure for conserving insectivorous predators (Mata et al., 2017 ). Together, these patterns highlight that increasing native vegetation diversity, reducing light and chemical pollution, restoring ecological continuity, and improving wetland and riparian habitats are essential steps to sustain insectivorous birds and bats. Finally, integrating functional traits into the design and management of multifunctional urban spaces could help support low-dispersal bird and bat species in UHIs and other highly urbanised areas. By increasing the local availability of food and nesting resources in these dense urban patches, species with limited dispersal capacity may be able to colonise and persist in sites that are currently beyond their reach. Studies of multifunctional urban green–blue infrastructure demonstrate how explicit design, implementation and management of multiple ecosystem services can support urban biodiversity (Cook et al., 2024 ; Vierikko et al. 2014 ). For example, in the GREEN SURGE Urban Learning Labs, pilot green–blue projects combining vegetation and water features provided habitat together with social and climatic benefits, confirming that biodiversity-friendly multifunctionality is achievable. Such conservation solutions need inter- and transdisciplinary research that effectively connects ecological knowledge with urban planning and decision-making. Declarations Funding T his work was funded by Grand Poitiers Communauté Urbaine, the Nouvelle Aquitaine Region, the University of Poitiers as well as RURALITES and EBI Laboratories. We also thank the Agence Nationale de la Recherche (Grant No. ANR-21-CE32-0002-01 [RECODE] to N.B.), the Office Français de la Biodiversité, the intramural Funds from the University of Poitiers (UP-Squared: INOVIE and ERI: ONE CITY ), the European Regional Development Fund (FEDER), the Chaire Biodiversité of the University of Poitiers and finally, the intramural Funds from the French National Centre for Scientific Research (CNRS). Competing Interests Authors declare no conflict of interest. Author Contributions Sophie Beltran-Bech and Nicolas Bech obtained the funding.Marina Querejeta, Elie Morin, Nicolas Bech and Sophie Beltran-Bech contributed to the study conception and design. Simon Chapenoire and Alice Chéron carried out the sampling. Marina Querejeta analysed the data. Marina Querejeta, Elie Morin, Nicolas Bech and Sophie Beltran-Bech contributed to the interpretation of results. Marina Querejeta led the writing of the manuscript. All authors contributed critically to the drafts and gave final approval for publication. All authors take responsibility for the work’s integrity and will address any issues concerning its accuracy. Data availability statement: Raw data has been deposited in figshare : https://figshare.com/s/ee685a6c019f2024513a References Amiot C, Harmange C, Ji W (2022) Morphological differences along a chronological gradient of urbanisation in an endemic insectivorous bird of New Zealand. Urban Ecosyst 25(2):465–475. https://doi.org/10.1007/s11252-021-01156-w Ancillotto L, Bosso L, Salinas-Ramos VB, Russo D (2019) The importance of ponds for the conservation of bats in urban landscapes. Landsc Urban Plann 190:103607. https://doi.org/10.1016/j.landurbplan.2019.103607 Ancillotto L, Tomassini A, Russo D (2015) The fancy city life: Kuhl’s pipistrelle, Pipistrellus kuhlii, benefits from urbanisation. Wildl Res 42(7):598–606. https://doi.org/10.1071/WR15003 Aram F, Higueras García E, Solgi E, Mansournia S (2019) Urban green space cooling effect in cities. Heliyon 5(4):e01339. https://doi.org/10.1016/j.heliyon.2019.e01339 Arango A, Pinto-Ledezma J, Rojas-Soto O, Lindsay AM, Mendenhall CD, Villalobos F (2022) Hand-Wing Index as a surrogate for dispersal ability: the case of the Emberizoidea (Aves: Passeriformes) radiation. Biol J Linn Soc 137. https://doi.org/10.1093/biolinnean/blac071 Aronson MFJ, Sorte L, Nilon FA, Katti CH, Goddard M, Lepczyk MA, Warren CA, Williams PS, Cilliers NSG, Clarkson S, Dobbs B, Dolan C, Hedblom R, Klotz M, Kooijmans S, Kühn JL, MacGregor-Fors I, McDonnell I, Mörtberg M, Winter U (2014) M. A global analysis of the impacts of urbanization on bird and plant diversity reveals key anthropogenic drivers. Proceedings of the Royal Society B: Biological Sciences , 281 (1780), 20133330. https://doi.org/10.1098/rspb.2013.3330 Avila-Flores R, Fenton MB (2005) USE OF SPATIAL FEATURES BY FORAGING INSECTIVOROUS BATS IN A LARGE URBAN LANDSCAPE. J Mammal 86(6):1193–1204. https://doi.org/10.1644/04-MAMM-A-085R1.1 Barataud M (2020) Écologie acoustique des Chiroptères d’Europe. Identification des espèces, étude de leurs habitats et comportements de chasse (P.; B. M. Muséum national d’Histoire naturelle (ed.); Fourth) Barnagaud J-Y, Devictor V, Jiguet F, Barbet-Massin M, Le Viol I, Archaux F (2012) Relating Habitat and Climatic Niches in Birds. PLoS ONE 7(3):e32819. https://doi.org/10.1371/journal.pone.0032819 Barton K, Barton MK (2015) Package ‘mumin’, vol 1. Version, p 439. 18 Basile M (2022) Rare species disproportionally contribute to functional diversity in managed forests. Sci Rep 12(1):5897. https://doi.org/10.1038/s41598-022-09624-9 Briones-Salas M, Medina-Cruz GE, Martin-Regalado CN (2024) Taxonomic, Functional, and Phylogenetic Diversity of Bats in Urban and Suburban Environments in Southern México. Diversity 16(9):527. https://doi.org/10.3390/d16090527 Brown LM, Graham CH (2015) Demography, traits and vulnerability to urbanization: can we make generalizations? J Appl Ecol 52(6):1455–1464. https://doi.org/10.1111/1365-2664.12521 Bunkley JP, McClure CJW, Kleist NJ, Francis CD, Barber JR (2015) Anthropogenic noise alters bat activity levels and echolocation calls. Global Ecol Conserv 3:62–71. https://doi.org/10.1016/j.gecco.2014.11.002 Buron R, Hostetler ME, Andreu M (2022) Urban forest fragments vs residential neighborhoods: Urban habitat preference of migratory birds. Landsc Urban Plann 227:104538. https://doi.org/10.1016/j.landurbplan.2022.104538 Cardinale BJ, Duffy JE, Gonzalez A, Hooper DU, Perrings C, Venail P, Narwani A, Mace GM, Tilman D, Wardle DA, Kinzig AP, Daily GC, Loreau M, Grace JB, Larigauderie A, Srivastava DS, Naeem S (2013) Biodiversity loss and its impact on humanity. Nature 486(7401):59–67. https://doi.org/10.1038/nature11148 Cisneros LM, Fagan ME, Willig MR (2016) Environmental and spatial drivers of taxonomic, functional, and phylogenetic characteristics of bat communities in human-modified landscapes. PeerJ 4:e2551. http://doi.org/10.7717/peerj.2551 Claramunt S, Hong M, Bravo A (2022) The effect of flight efficiency on gap-crossing ability in Amazonian forest birds. Biotropica 54(4):860–868. https://doi.org/10.1111/btp.13109 Cook LM, Good KD, Moretti M, Kremer P, Wadzuk B, Traver R, Smith V (2024) Towards the intentional multifunctionality of urban green infrastructure: a paradox of choice? npj Urban Sustain 4(1):12. https://doi.org/10.1038/s42949-024-00145-0 Craig EC, Elbin SB, Sparks JP, Curtis PD (2015) Identifying important foraging habitat for colonial waterbirds in an urban estuary: a stable isotope approach. Waterbirds 38(4):330–338. https://doi.org/10.1675/063.038.0410 de Bello F, Carmona CP, Lepš J, Szava-Kovats R, Pärtel M (2016) Functional diversity through the mean trait dissimilarity: resolving shortcomings with existing paradigms and algorithms. Oecologia 180(4):933–940. https://doi.org/10.1007/s00442-016-3546-0 Denzinger A, Schnitzler H-U (2013) Bat guilds, a concept to classify the highly diverse foraging and echolocation behaviors of microchiropteran bats. Frontiers in Physiology , 4 . https://doi.org/10.3389/fphys.2013.00164 Dinno A, Dinno MA (2017) Package ‘dunn. test’. CRAN Repos 10:1–7 Egert-Berg K, Handel M, Goldshtein A, Eitan O, Borissov I, Yovel Y (2021) Fruit bats adjust their foraging strategies to urban environments to diversify their diet. BMC Biol 19(1):123. https://doi.org/10.1186/s12915-021-01060-x Eötvös CB, Magura T, Lövei GL (2018) A meta-analysis indicates reduced predation pressure with increasing urbanization. Landsc Urban Plann 180:54–59. https://doi.org/10.1016/j.landurbplan.2018.08.010 Fischer FM, de Bello F (2023) On the uniqueness of functional redundancy. Npj Biodivers 2(1):23. https://doi.org/10.1038/s44185-023-00015-5 Gosler AG, Greenwood JJD, Baker JK, Davidson NC (1998) The field determination of body size and condition in passerines: A report to the British Ringing Committee. Bird Study 45:92–103 Guetté A, Gaüzère P, Devictor V, Jiguet F, Godet L (2017) Measuring the synanthropy of species and communities to monitor the effects of urbanization on biodiversity. Ecol Ind 79:139–154. https://doi.org/10.1016/j.ecolind.2017.04.018 Hage SR, Jiang T, Berquist SW, Feng J, Metzner W (2013) Ambient noise induces independent shifts in call frequency and amplitude within the Lombard effect in echolocating bats. Proceedings of the National Academy of Sciences , 110 (10), 4063–4068. https://doi.org/10.1073/pnas.1211533110 Hale JD, Fairbrass AJ, Matthews TJ, Sadler JP (2012) Habitat Composition and Connectivity Predicts Bat Presence and Activity at Foraging Sites in a Large UK Conurbation. PLoS ONE 7(3):e33300. https://doi.org/10.1371/journal.pone.0033300 Hartig F (2022) DHARMa: residual diagnostics for hierarchical (multi-level/mixed) regression models. R package (version 0.4. 6.) Hughes M, Brown SK, Foster-Plume D, Lee D, Redfern T, Maddock S, Young CH (2024) Big city bats: Species-specific effects of the urban matrix on forearm length and fat stores of bats in the West Midlands, United Kingdom (Chiroptera: Vespertilionidae). Lynx New Ser 54(1):75–82. https://doi.org/10.37520/lynx.2023.005 Jame A, Noizat C, Morin E, Paulhac H, Guinard Y, Rodier T, Michenaud R, Pigeault R, Yengué J-L, Preux T, Royoux D, Beltran-Bech S, Bech N (2024) A combination of methods for mapping heat and cool areas in past and current urban landscapes of Poitiers (France). Ecol Ind 167:112712. https://doi.org/10.1016/j.ecolind.2024.112712 Johnson MTJ, Munshi-South J (2017) Evolution of life in urban environments. Science 358(6363). https://doi.org/10.1126/science.aam8327 Jung K, Threlfall CG (2016) Urbanisation and Its Effects on Bats—A Global Meta-Analysis. In Bats in the Anthropocene: Conservation of Bats in a Changing World (pp. 13–33). Springer International Publishing. https://doi.org/10.1007/978-3-319-25220-9_2 Jung K, Threlfall CG (2018) Trait-dependent tolerance of bats to urbanization: a global meta-analysis. Proceedings of the Royal Society B: Biological Sciences , 285 (1885), 20181222. https://doi.org/10.1098/rspb.2018.1222 Kark S, Iwaniuk A, Schalimtzek A, Banker E (2007) Living in the city: can anyone become an ‘urban exploiter’’?’. J Biogeogr 34(4):638–651. https://doi.org/10.1111/j.1365-2699.2006.01638.x Kassambara A (2023) ggpubr: ggplot2 Based Publication Ready Plots. R package (version 0.6.0) Kembel SW, Cowan PD, Helmus MR, Cornwell WK, Morlon H, Ackerly DD, Blomberg SP, Webb CO (2010) Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26(11):1463–1464. https://doi.org/10.1093/bioinformatics/btq166 Kondratyeva A, Knapp S, Durka W, Kühn I, Vallet J, Machon N, Martin G, Motard E, Grandcolas P, Pavoine S (2020) Urbanization Effects on Biodiversity Revealed by a Two-Scale Analysis of Species Functional Uniqueness vs. Redundancy. Frontiers in Ecology and Evolution , 8 . https://doi.org/10.3389/fevo.2020.00073 Laureto LMO, Cianciaruso MV, Samia DSM (2015) Functional diversity: an overview of its history and applicability. Natureza Conservação 13(2):112–116. https://doi.org/10.1016/j.ncon.2015.11.001 Lee ATK, Ottosson U, Jackson C, Shema S, Reynolds C (2021) Urban areas have lower species richness, but maintain functional diversity: insights from the African Bird Atlas Project. Ostrich 92(1):1–15. https://doi.org/10.2989/00306525.2021.1902876 Leitão RP, Zuanon J, Villéger S, Williams SE, Baraloto C, Fortunel C, Mendonça FP, Mouillot D (2016) Rare species contribute disproportionately to the functional structure of species assemblages. Proceedings of the Royal Society B: Biological Sciences , 283 (1828), 20160084. https://doi.org/10.1098/rspb.2016.0084 Li M, Cao Y, Dai J, Song J, Liang M (2025) A Comprehensive Review of Urban Expansion and Its Driving Factors. Land 14(8):1534. https://doi.org/10.3390/land14081534 Liker A, Papp Z, Bókony V, Lendvai AZ (2008) Lean birds in the city: body size and condition of house sparrows along the urbanization gradient. J Anim Ecol 77(4):789–795. https://doi.org/10.1111/j.1365-2656.2008.01402.x Lin L, Liu Y, Lin H, Kang B (2024) Considering species functional and phylogenetic rarity in the conservation of fish biodiversity. Divers Distrib 30(3):e13804. https://doi.org/10.1111/ddi.13804 Losos JB (2008) Phylogenetic niche conservatism, phylogenetic signal and the relationship between phylogenetic relatedness and ecological similarity among species. Ecol Lett 11(10):995–1003. https://doi.org/10.1111/j.1461-0248.2008.01229.x Magneville C, Loiseau N, Albouy C, Casajus N, Claverie T, Escalas A, Leprieur F, Maire E, Mouillot D, Villéger S (2022) mFD: an R package to compute and illustrate the multiple facets of functional diversity. Ecography 2022(1). https://doi.org/10.1111/ecog.05904 Mata L, Threlfall CG, Williams NS, Hahs AK, Malipatil M, Stork NE, Livesley SJ (2017) Conserving herbivorous and predatory insects in urban green spaces. Sci Rep 7(1):40970. https://doi.org/10.1038/srep40970 Mathews F, Roche N, Aughney T, Jones N, Day J, Baker J, Langton S (2015) Barriers and benefits: implications of artificial night-lighting for the distribution of common bats in Britain and Ireland. Philosophical Trans Royal Soc B: Biol Sci 370(1667):20140124. https://doi.org/10.1098/rstb.2014.0124 Meillère A, Brischoux F, Parenteau C, Angelier F (2015) Influence of urbanization on body size, condition, and physiology in an urban exploiter: a multi-component approach. PLoS ONE 10(8):e0135685. https://doi.org/10.1371/journal.pone.0135685 Mimet A, Kerbiriou C, Simon L, Julien J-F, Raymond R (2020) Contribution of private gardens to habitat availability, connectivity and conservation of the common pipistrelle in Paris. Landsc Urban Plann 193:103671. https://doi.org/10.1016/j.landurbplan.2019.103671 Møller AP (2009) Successful city dwellers: a comparative study of the ecological characteristics of urban birds in the Western Palearctic. Oecologia 159(4):849–858. https://doi.org/10.1007/s00442-008-1259-8 Monge-González ML, Guerrero-Ram\’\irez N, Krömer T, Kreft H, Craven D (2021) Functional diversity and redundancy of tropical forests shift with elevation and forest-use intensity. J Appl Ecol 58(9):1827–1837. https://doi.org/10.1111/1365-2664.13955 Neate-Clegg MHC, Tonelli BA, Youngflesh C, Wu JX, Montgomery GA, Şekercioğlu ÇH, Tingley MW (2023) Traits shaping urban tolerance in birds differ around the world. Curr Biol 33(9):1677–1688e6. https://doi.org/10.1016/j.cub.2023.03.024 Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’hara RB, Simpson GL, Solymos P, Stevens MHH, Wagner H (2013) & others. Package ‘vegan.’ Community Ecology Package, Version , 2 (9), 1–295 Oliveira Hagen E, Hagen O, Ibáñez-Álamo JD, Petchey OL, Evans KL (2017) Impacts of Urban Areas and Their Characteristics on Avian Functional Diversity. Frontiers in Ecology and Evolution , 5 . https://doi.org/10.3389/fevo.2017.00084 Palacio FX, Ibañez LM, Maragliano RE, Montalti D (2018) Urbanization as a driver of taxonomic, functional, and phylogenetic diversity losses in bird communities. Can J Zool 96(10):1114–1121. https://doi.org/10.1139/cjz-2018-0008 Pauw A, Louw K (2012) Urbanization drives a reduction in functional diversity in a guild of nectar-feeding birds. Ecol Soc 17(2). http://dx.doi.org/10.5751/ES-04758-170227 Petchey OL, Gaston KJ (2002) Extinction and the loss of functional diversity. Proceedings of the Royal Society of London. Series B: Biological Sciences , 269 (1501), 1721–1727. https://doi.org/10.1098/rspb.2002.2073 Piano E, De Wolf K, Bona F, Bonte D, Bowler DE, Isaia M, Lens L, Merckx T, Mertens D, Van Kerckvoorde M (2017) & others. Urbanization drives community shifts towards thermophilic and dispersive species at local and landscape scales. Global Change Biology , 23 (7), 2554–2564. https://doi.org/10.1111/gcb.13606 Querejeta M, Jame A, Morin E, Chapenoire S, Chéron A, Paulhac H, Ramdani MS, Guinard Y, Preux T, Michenaud R, Yengué J-L, Royoux D, Rodier T, Bech N, Beltran-Bech S (2025) Should I Stay or Should I Go: How Urban Heat Gradients Affect the Local Distribution of Birds and Bats. http://dx.doi.org/10.2139/ssrn.5206711 R Core Team (2024) R: A language and environment for statistical computing. (Version 4.4. 1). R foundation for statistical computing., Vienna Russo D, Ancillotto L (2015) Sensitivity of bats to urbanization: a review. Mammalian Biology 80(3):205–212. https://doi.org/10.1016/j.mambio.2014.10.003 Schille L, Paquette A, Marcotte G, Ouellet H, Cobus S, Barbaro L, Castagneyrol B (2025) Urban tree diversity fosters bird insectivory despite a loss in bird diversity with urbanization. Landsc Urban Plann 256:105274. https://doi.org/10.1016/j.landurbplan.2024.105274 Sol D, Bartomeus I, González-Lagos C, Pavoine S (2017) Urbanisation and the loss of phylogenetic diversity in birds. Ecol Lett 20(6):721–729. https://doi.org/10.1111/ele.12769 Sol D, González-Lagos C, Moreira D, Maspons J, Lapiedra O (2014) Urbanisation tolerance and the loss of avian diversity. Ecol Lett 17(8):942–950. https://doi.org/10.1111/ele.12297 Sol D, Trisos C, Múrria C, Jeliazkov A, González-Lagos C, Pigot AL, Ricotta C, Swan CM, Tobias JA, Pavoine S (2020) The worldwide impact of urbanisation on avian functional diversity. Ecol Lett 23(6):962–972. https://doi.org/10.1111/ele.13495 Starik N, Göttert T (2022) Bats adjust echolocation and social call design as a response to urban environments. Frontiers in Ecology and Evolution , 10 . https://doi.org/10.3389/fevo.2022.939408 Straka TM, Lentini PE, Lumsden LF, Buchholz S, Wintle BA, van der Ree R (2020) Clean and green urban water bodies benefit nocturnal flying insects and their predators, insectivorous bats. Sustainability 12(7):2634. https://doi.org/10.3390/su12072634 Suarez-Rubio M, Ille C, Bruckner A (2018) Insectivorous bats respond to vegetation complexity in urban green spaces. Ecol Evol 8(6):3240–3253. https://doi.org/10.1002/ece3.3897 Teeling EC, Springer MS, Madsen O, Bates P, O’Brien SJ, Murphy WJ (2005) A molecular phylogeny for bats illuminates biogeography and the fossil record. Science 307:580–584. https://doi.org/10.1126/science.1105113 Tiago P, Leal AI, Silva CM (2024) Assessing ecological gains: A review of How arthropods, bats and birds benefit from green roofs and walls. Environments 11(4):76. https://doi.org/10.3390/environments11040076 Tyler T (2020) Relationship between moth (night active Lepidoptera) diversity and vegetation characteristics in southern Sweden. J Insect Conserv 24(6):1005–1015. https://doi.org/10.1007/s10841-020-00270-y United Nations, & Department of Economic and Social Affairs (2019) World Population Prospects 2019 . United Nations. https://population.un.org/wpp/ Vähätalo AV, Pulli A, Kulmala T, Marin R, Haimi J (2024) Urbanization related changes in lepidopteran community. Urban Ecosyst 27(2):377–386. https://doi.org/10.1007/s11252-023-01456-3 Vierikko K, Niemela J, Buizer IM, Elands BHM (2014) Green Infrastructure and Urban Biodiversity for Sustainable Urban Development and the Green Economy (GREEN SURGE)–Is there place for biocultural diversity in the cities? In Proceedings of the 7th Annual ESP Conference 2014: Local action for the common good (pp. 32–32) Violle C, Thuiller W, Mouquet N, Munoz F, Kraft NJB, Cadotte MW, Livingstone SW, Mouillot D (2017) Functional rarity: the ecology of outliers. Trends Ecol \& Evol 32(5):356–367 Wang Y, Naumann U, Wright S, Eddelbuettel D, Warton D (2017) mvabund: Statistical methods for analysing multivariate abundance data. R Package Version, 3 (3) Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, Grolemund G, Hayes A, Henry L, Hester J (2019) & others. Welcome to the Tidyverse. Journal of Open Source Software , 4 (43), 1686 Wickham H, François R, Henry L, Müller K (2021) dplyr: A Grammar of Data Manipulation. R package version 1.0.5. Wolf JM, Jeschke JM, Voigt CC, Itescu Y (2022) Urban affinity and its associated traits: A global analysis of bats. Glob Change Biol 28(19):5667–5682. https://doi.org/10.1111/gcb.16320 Wood H, Cousins SAO (2023) Variability in bat morphology is influenced by temperature and forest cover and their interactions. Ecol Evol 13(1). https://doi.org/10.1002/ece3.9695 Zabala-Forero F, Cortes-Gomez AM, Urbina-Cardona N (2025) How low-abundance amphibians shape functional diversity across tropical forest succession stages? Ecol Ind 171:113140. https://doi.org/10.1016/j.ecolind.2025.113140 Additional Declarations No competing interests reported. Supplementary Files SupportingInformationB.docx SupportingInformationA.docx Cite Share Download PDF Status: Published Journal Publication published 23 Mar, 2026 Read the published version in Biodiversity and Conservation → Version 1 posted Editorial decision: Revision requested 03 Jan, 2026 Reviews received at journal 02 Jan, 2026 Reviews received at journal 25 Dec, 2025 Reviewers agreed at journal 05 Dec, 2025 Reviewers agreed at journal 02 Dec, 2025 Reviewers invited by journal 02 Dec, 2025 Editor assigned by journal 02 Dec, 2025 Submission checks completed at journal 25 Nov, 2025 First submitted to journal 21 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Each ellipse represents a type of urban point, Urban Heat Island (UHI) or Urban Cool Island (UCI).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-8172612/v1/4abb2533c2d9e66b41159710.png"},{"id":97471922,"identity":"9ee7f424-8c78-4864-95d3-f967bd9023f1","added_by":"auto","created_at":"2025-12-04 17:51:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":56075,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap representing the standardised model coefficients for each bat species functional traits resulting from the fourth-corner analysis adding a LASSO PENALTY. Categorical variables have been converted to dummy variables for each of their factors.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-8172612/v1/c393928e7d2ce1952bb5eb10.png"},{"id":97471923,"identity":"47ffe870-3605-4290-85f3-85da0a3ca668","added_by":"auto","created_at":"2025-12-04 17:51:30","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":70653,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplots representing the differences between the two types of urban points, Urban Heat Islands (UHIs) and Urban Cool Islands (UCIs) of the Functional Redundancy (FRed) for A) bird and B) bat assemblages. Signification according to Generalized Linear Models (GLMs) are placed over each plot when significant.\u003c/p\u003e","description":"","filename":"image3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8172612/v1/c424dc7c6f058c78f46b2d3d.jpeg"},{"id":97471925,"identity":"feb45be9-f5bd-4132-ada7-5f2d3bb73673","added_by":"auto","created_at":"2025-12-04 17:51:30","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":52720,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation plots between the First Component (PC1) of the urban landscape variables Principal Components Analysis (PCA) or “Rate of Artificialisation” with Redundancy (FRed) for A) birds and B) bats. Points are coloured by type of urban point, Urban Heat Island (UHI) or Urban Cool Island (UCI).\u003c/p\u003e","description":"","filename":"image4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8172612/v1/e2761ffc096255b06a2ceff9.jpeg"},{"id":97670487,"identity":"e6ada96b-c383-496f-b6f1-918f9d07eb1d","added_by":"auto","created_at":"2025-12-08 09:30:47","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":120265,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplots representing functional rarity metrics, Functional Distinctiveness (FDi) and Functional Scarcity (FSi), between the two types of urban points, Urban Heat Islands (UHIs) and Urban Cool Islands (UCIs) in urban A) bird and B) bat assemblages. Signification according to Generalized Linear Models (GLMs) are placed over each plot when significant.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-8172612/v1/8ea8279a56935d79e2b0a92e.png"},{"id":97471930,"identity":"43aa14cc-4276-44af-aae9-228a74e7c8c0","added_by":"auto","created_at":"2025-12-04 17:51:30","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":183574,"visible":true,"origin":"","legend":"\u003cp\u003eUrban\u003cstrong\u003e \u003c/strong\u003ebird and bat\u003cstrong\u003e \u003c/strong\u003ecorrelations between functional rarity metrics, Functional Distinctiveness (FDi) and Functional Scarcity (FSi) with the First Component (PC1) of the urban landscape variables Principal Components Analysis (PCA) or “Rate of Artificialisation”. Points are coloured by type of urban point, Urban Heat Island (UHI) or Urban Cool Island (UCI).\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-8172612/v1/7c6c4262629933dad5ef87fc.png"},{"id":105755397,"identity":"8c336ca3-6cb9-4ab5-914e-03321600fc8c","added_by":"auto","created_at":"2026-03-30 16:27:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1552776,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8172612/v1/78679bfa-af67-4f1c-8570-9dbbd00449f6.pdf"},{"id":97471924,"identity":"72918105-3a6e-4c18-90a6-60fa0b8e7f36","added_by":"auto","created_at":"2025-12-04 17:51:30","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":99917,"visible":true,"origin":"","legend":"","description":"","filename":"SupportingInformationB.docx","url":"https://assets-eu.researchsquare.com/files/rs-8172612/v1/3972bcc8c72ecef332f85fef.docx"},{"id":97471931,"identity":"6b8a3bcb-a3b0-44d9-9a7c-8555f0cf59d6","added_by":"auto","created_at":"2025-12-04 17:51:30","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":923050,"visible":true,"origin":"","legend":"","description":"","filename":"SupportingInformationA.docx","url":"https://assets-eu.researchsquare.com/files/rs-8172612/v1/19a8e752eac67c689db53779.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Traits and the City: functional trait space in urban bird and bat assemblages","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eHuman population is growing at an exponential rate (United Nations 2019), leading to profound and often irreversible changes in global land use, as natural habitats are increasingly replaced by human infrastructure (Li et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; United Nations \u0026amp; Department of Economic and Social Affairs 2019). Urbanisation is recognised as a major contributor to global biodiversity declines (Piano et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), often illustrated by the fact that only a subset of species can withstand such disturbances (Sol et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Understanding which species traits or environmental conditions enable some taxa to persist in, or exclude others from, urban ecosystems is, therefore, essential.\u003c/p\u003e\u003cp\u003eUrbanisation affects biodiversity in different ways across taxa. Some studies report increased abundance or richness at intermediate or high urban levels (Kondratyeva et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), whereas others show marked declines in species diversity and abundance (Sol et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). These contrasting patterns suggest that the effects of urban development on species assemblages are highly context-dependent, where \u0026ldquo;context\u0026rdquo; refers to both the taxon considered and the specific landscape or urban characteristics. However, certain functional traits or ecological functions may persist, or even be favoured, in highly urbanised environments, facilitating the colonisation of urban ecosystems (Brown \u0026amp; Graham \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe exploration of functional diversity allows us to evaluate ecosystem functions and processes through species\u0026rsquo; functional traits (Sol et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Indeed, trait diversity strongly influences ecosystem functions in multiple ways (Cardinale et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Generally, highly urbanised areas, experience declines in functional diversity due to a reduction in species with high trait divergence, making assemblages more homogeneous and, thus, less resilient to disturbances (Johnson \u0026amp; Munshi-South \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). At the same time, rare or low-abundance species have been recognised as crucial for maintaining functional diversity in ecosystems in some cases, as their distinctive traits can make outsized contributions to ecosystem services, and resilience (Leit\u0026atilde;o et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Lin et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zabala-Forero et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Yet the drivers of functional diversity in cities are complex and asymmetric, calling for further research to clarify these patterns and guide urban planning and conservation.\u003c/p\u003e\u003cp\u003eBirds and bats, as the sole flying vertebrates in temperate ecosystems, have successfully colonised urban environments (Guett\u0026eacute; et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Mimet et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Birds\u0026rsquo; ability to colonise cities depends on a specific combination of morphological traits, foraging and habitat breadth, geographical range size, nesting behaviour, and reproductive success (Kark et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Sol et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Along increasing gradients of urbanisation intensity, some studies have reported reductions in the functional diversity of bird assemblages (Aronson et al. 2020; Sol et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), whereas others have shown that urban areas can retain substantial levels of avian functional diversity (Oliveira Hagen et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Querejeta et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). \u0026ldquo;Urban winner\u0026rdquo; species are often characterised by generalist traits, which mainly represented by members of the Passeridae, Columbidae, Corvidae, and Sturnidae families (Guett\u0026eacute; et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Sol et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Certain functional traits may enable birds to respond adaptively to urban stressors, although behavioural plasticity has been less strongly associated with urban tolerance than previously thought (Guett\u0026eacute; et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Sol et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Such advantageous traits are typically linked to generalist resource use, while migratory species and those that nest in shrubs or on the ground are more closely associated with non-urban, natural forest habitats (Buron et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Neate-Clegg et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In the case of bats, a highly phylogenetically diverse group (Teeling et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), their functional responses to urban stressors have been shown to be species-specific (Ancillotto et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Jung \u0026amp; Threlfall \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Russo \u0026amp; Ancillotto \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), with certain species possessing specific functional traits that make them less vulnerable to urban landscapes than others (Avila-Flores \u0026amp; Fenton \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Jung \u0026amp; Threlfall \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Despite this high variability, urban-tolerant bat species tend to share a set of traits. In general, urban bats fly faster (Avila-Flores \u0026amp; Fenton \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), though with less agility (Ancillotto et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Egert-Berg et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Jung \u0026amp; Threlfall, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and produce lower-frequency echolocation calls (Threlfall et al. 2011). Regarding feeding behaviour, species that forage in open or edge spaces and exhibit flexible roosting strategies (Jung \u0026amp; Threlfall \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), such as using human-associated structures like caves, tunnels, or abandoned buildings (Briones-Salas et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), are also more successful in urban environments.\u003c/p\u003e\u003cp\u003eDespite being the most conspicuous urban assemblages, birds and bats have rarely been studied together in urban environments (Jung \u0026amp; Threlfall \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Querejeta et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Tiago et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). To address this gap, we surveyed birds\u0026rsquo; and bats\u0026rsquo; assemblages to explore their functional space. Specifically, we examined the effect of Urban Heat Islands (UHIs) and Urban Cool Islands (UCIs) on urban bird and bat assemblages in the medium-size city of Poitiers, France. UHIs can be defined as areas within the cities, which are experiencing a rise of temperatures, mainly due to highly dense urbanisation, human activities and land modification. On contrast, UCIs are urban sites represented by less rise of temperature in comparison to UHIs, due to a lighter form of urbanisation (Jame et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Using UHIs as a proxy for highly urbanised areas, Querejeta et al. (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) analysed the taxonomic, phylogenetic, and functional diversity of birds and bats in the study area of Poitiers, France, using the same field sampling and biodiversity dataset as the present study. Results showed that bat taxonomic, phylogenetic, and functional diversity decline within UHIs and along an artificialisation gradient, while in birds only taxonomic diversity declines, with phylogenetic diversity unchanged and functional diversity even higher in UHIs. In this context, this study aims to address the following specific objectives: (1) determine the differences between UHIs and UCIs (as a proxy for contrasting urban microclimates), as well as along an artificialisation gradient in functional diversity and redundancy (2) to examine whether rare species drive functional diversity within the urban ecosystem; (3) to uncover functional traits that confer either tolerance or sensitivity to extreme urbanisation and its associated microclimatic effects; and (4) to identify shared functional traits or ecological strategies, in order to determine whether specific traits are similarly favoured or filtered out in both urban bird and bat assemblages.\u003c/p\u003e\u003cp\u003eAs bats have been reported to be more vulnerable to dense urbanisation(Aronson et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Jung et al. 2018), we hypothesized that the functional response would differ between bird and bat urban assemblages, with distinct functional traits conferring tolerance to urban stressors. Moreover, we hypothesized that functionally rare species (Basile \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Leit\u0026atilde;o et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) would drive functional diversity in both urban bird communities, while the effect of landscape variables and dominant or abundant species would be the most important driver in the case of bats (Cisneros et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e"},{"header":"2. Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Study area and design\u003c/h2\u003e\u003cp\u003eThe spatial distribution of UHIs and UCIs was determined using high-resolution mapping based primarily on Land Surface Temperature (LST) and the Heat Mitigation Index (HMI) (Jame et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Then, urban bird and bat communities were sampled at 25 UHIs and 25 UCIs previously identified in Poitiers, France. The abundance of birds was surveyed following the French \u003cem\u003eEPOC\u003c/em\u003e protocol (Fontaine et al., 2020) during two periods in spring 2023 (April and June), with species identified by song or sight and breeding status recorded. The frequency of bats was sampled acoustically between June and August 2023 using \u003cem\u003eTeensyRecorders\u003c/em\u003e deployed for three nights per site, with one standardised night retained per point. Sonograms were processed with the software \u003cem\u003eKaleidoscope\u003c/em\u003e and verified manually (Barataud M., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). While samples are broadly identical (i.e. located in UHIs and UCIs) for both assemblages, bat sampling sites have been shifted from bird sampling locations in certain geographical points, as bat acoustic recorders must be place in safe and fresh places. A spatial autocorrelation analysis employing the Procrustes method was conducted to assess whether differences in the composition of bird and bat assemblages were related to the geographic distances among urban site types, implemented via the \u003cem\u003eprotest\u003c/em\u003e function in the \u003cem\u003evegan\u003c/em\u003e R package (Oksanen et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Data has been deposited in \u003cem\u003efigshare\u003c/em\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://figshare.com/s/ee685a6c019f2024513a.2.2\u003c/span\u003e\u003cspan address=\"https://figshare.com/s/ee685a6c019f2024513a.2.2\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. \u003cem\u003eLandscape urban variables\u003c/em\u003e\u003c/p\u003e\u003cp\u003eLandscape environmental variables were estimated separately for birds and bats within a 200 m buffer around each sampling location. This scale is relevant to birds, bats, and their prey. On one hand, we used a high-resolution land cover map (\u003cem\u003ei.e.\u003c/em\u003e 1 m resolution) to extract vegetation structure (including tree cover and strata diversity), built environment density, and distances to rural and aquatic. To assess the differences in landscape heterogeneity between sampling sites located in UHIs and UCIs, we performed a multivariate dispersion analysis on a Euclidean distance matrix followed by a permutational test (999 iterations) using \u003cem\u003evegan\u003c/em\u003e R package, respectively (Oksanen et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). To evaluate how sensitive our results were to sample size, we implemented a custom sensitivity analysis that repeatedly subsamples the dataset and re-runs the multivariate dispersion analysis (200 iterations with 999 permutations each) using the packages \u003cem\u003evegan\u003c/em\u003e (Oksanen et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and \u003cem\u003edplyr\u003c/em\u003e (Wickham et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).All analyses were performed in R (R Core Team 2025).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Fourth-corner analysis\u003c/h2\u003e\u003cp\u003eTo explore how species\u0026rsquo; functional traits mediate their response to urban landscape variables, we applied a fourth-corner analysis using the \u003cem\u003emvabund\u003c/em\u003e R package (Wang et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). To simplify the analysis, we retained only those urban landscape variables that were significantly correlated with functional diversity, as assessed using the \u003cem\u003eggpubr\u003c/em\u003e R package (Kassambara 2020) (Supporting Information B, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e): density of building infrastructures, of impervious surfaces, of overall vegetation, of tree vegetation, distance to natural and semi-natural areas and to permanent and temporal wetlands. To include categorical traits in the analysis, we converted them into binary (dummy) variables. We selected the strongest trait-environment interactions by fitting the model using a LASSO-penalized regression. However, because the LASSO approach does not provide formal significance tests, we then re-fitted the model without the penalty to assess the statistical significance of the associations using a permutation-based ANOVA.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Landscape Principal Component Analysis (PCA)\u003c/h2\u003e\u003cp\u003eTo reduce dimensionality and summarise environmental variables, we performed a Principal Component Analysis (PCA) in which the first axis (PC1) represented the landscape composition or \u0026ldquo;Rate of Artificialisation\u0026rdquo;, and the second axis (PC2) reflected the \u0026ldquo;Landscape Configuration\u0026rdquo; or PC2. In both assemblages, PC1 is mainly driven by density of vegetation, tree vegetation, impervious surfaces and buildings while PC2 is driven mainly by diversity of vegetation strata and distance to permanent wetlands. All subsequent analyses on urban landscape have been done using urban PCA components, PC1 and PC2.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.6. Bird and bat functional traits and alpha-diversity metrics\u003c/h2\u003e\u003cp\u003eWe used bird and bat functional traits, which could potentially be associated with responses to urbanisation, to compute functional alpha-diversity metrics. In the case of birds, 14 functional traits were used, nine quantitative and five nominal, whereas for bats, 12 functional traits were compiled, of which eight are quantitative and four nominal (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Detailed information about bird and bat functional traits can be found in Supporting Information B, Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary table of functional traits used in this study for urban birds\u0026rsquo; and bats\u0026rsquo; assemblages. Categorical traits are collapsed in one type of category.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrait category\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTrait type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBird traits\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBat traits\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMorphological\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuantitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBeak length, tarsus length, Hand-Wing index (HWI), body mass\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eForearm length, body mass\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLife-history\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuantitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eClutch size, lifespan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLifespan\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHabitat-related\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuantitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpecies Specialisation Index (SSI), Species Temperature Index (STI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSpecies Specialisation Index (SSI), Species Temperature Index (STI)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEcholocation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuantitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCall duration, call peak frequency\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGeographic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuantitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGeographic range size\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGeographic range size\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiverse categories\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategorical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHabitat type, migratory behaviour, main lifestyle, trophic level, feeding niche\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCall type, primary hibernation roost, main maternity roost, main prey type\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTo quantify functional alpha-diversity, we computed pairwise species distances using the Gower method based on functional traits (Magneville et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These distances, combined with species abundance (birds) or frequency (bats), were used to construct the functional space via Principal Coordinates Analysis (PCoA). Functional Richness (FRic) and Mean Functional Distance (MFD), representing respectively the occupied trait space and mean functional dissimilarity among species (Vill\u0026eacute;ger et al. 2008; Kembel et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), were computed using \u003cem\u003emFD\u003c/em\u003e R package (Magneville et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Standardised effect sizes were derived from null models, except for MFD. Functional Redundancy (FRed) was defined as 1 \u0026ndash; (FRic/species richness), indicating the extent of overlap in functional roles.\u003c/p\u003e\u003cp\u003eTo assess the functional rarity of urban bird and bat local assemblages, we computed functional distinctiveness and scarcity for each species using the \u003cem\u003efunrar\u003c/em\u003e R package (Violle et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). These metrics were calculated based on a Gower distance matrix of species traits (as described above). Functional Distinctiveness (FDi) quantifies how functionally different a species is from the other species in the same community, with values ranging from 0 (not functionally distinct) to 1 (highly distinct). Functional Scarcity (FSi) measures how locally rare a species is relative to the other species in the community, based on its relative abundance, also ranging from 0 (locally abundant) to 1 (highly scarce). Furthermore, we identified the top 10% most distinctive and most scarce species within each assemblage and recalculated all functional alpha-diversity metrics after simulating the loss of these species. We then used the Kruskal\u0026ndash;Wallis test followed by Dunn\u0026rsquo;s post hoc test, via \u003cem\u003eFSA\u003c/em\u003e R package (Dinno \u0026amp; Dinno \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), to assess whether the loss of these rare species significantly affected functional diversity. Finally, we calculated the percentage contribution of these species to the functional alpha-diversity metrics that were significantly affected by the loss of distinctive and/or scarce species. These analyses were performed using a customized R script, leveraging the \u003cem\u003edplyr\u003c/em\u003e and \u003cem\u003etidyr\u003c/em\u003e R packages (Wickham et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGeneralized Linear Models (GLMs) were fitted to assess whether functional alpha diversity and rarity metrics were primarily influenced by the type of urban site (UHI or UCI), the urban PCA components, PC1 and PC2. Models were built using the \u003cem\u003eglm\u003c/em\u003e function from the base R \u003cem\u003estats\u003c/em\u003e package, with functional alpha-diversity and rarity metrics as dependent variables, and urban PCA components as fixed effects. Model selection was based on the corrected Akaike Information Criterion (AICc), using the dredge and select.models functions from the \u003cem\u003eMuMIn\u003c/em\u003e package (Barton \u0026amp; Barton \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). All dependent variables were modelled assuming a Gaussian distribution with an identity link function. Model diagnostics, including checks for overdispersion, outliers, and zero-inflation, were performed using the \u003cem\u003eDHARMa\u003c/em\u003e package (Hartig \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). All analyses were performed using \u003cem\u003eR version 4.4.1\u003c/em\u003e (R Core Team \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.7. Bird and bat functional beta-diversity\u003c/h2\u003e\u003cp\u003eTo assess functional beta-diversity among bird and bat communities, we used a distance-based Redundancy Analysis (dbRDA) based on Bray\u0026ndash;Curtis distances, implemented via the \u003cem\u003evegan\u003c/em\u003e R package (Oksanen et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.8. Community Weighted Means of functional traits\u003c/h2\u003e\u003cp\u003eTo evaluate whether certain functional traits were conserved within UHIs or urban cool islands (UCIs) in bird and bat assemblages, we calculated community-weighted means (CWMs) for each quantitative trait using \u003cem\u003edplyr\u003c/em\u003e R package (Wickham et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). For birds, these included indices describing temperature and habitat specialization, body mass, morphological dimensions (beak, tarsus, and Hand-Wing Index), reproductive traits (egg number and lifespan), and geographic range. For bats, we computed CWMs for temperature and habitat specialisation, body mass, forearm length, geographic range, lifespan, and echolocation characteristics (call duration and peak frequency).\u003c/p\u003e\u003cp\u003e\u003cem\u003e2.9. Correlations and effects of the type of urban point and urban landscape variables on CWMs of functional traits\u003c/em\u003e\u003c/p\u003e\u003cp\u003ePearson gradient correlations were also performed between the community-weighted means of quantitative functional traits and the landscape principal components: \u0026ldquo;Rate of Artificialisation\u0026rdquo; (PC1) and \u0026ldquo;Landscape Configuration\u0026rdquo; (PC2). We computed correlations and displayed them as scatterplots using the \u003cem\u003eggpubr\u003c/em\u003e package in R (Kassambara \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Moreover, we repeated the Generalized Linear Model (GLM) analyses described above (section \u003cspan refid=\"Sec6\" class=\"InternalRef\"\u003e2.6\u003c/span\u003e), using CWMs of functional traits as dependent variables, with the type of urban point, UHI or UCI, and urban PCA components as fixed effects.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Differences in landscape heterogeneity and functional trait space between UHIs and UCIs\u003c/h2\u003e\u003cp\u003eThe lack of significance in the Procrustes analyses suggests that spatial proximity did not influence the observed differences in bird (Protest R\u0026thinsp;=\u0026thinsp;0.26, p\u0026thinsp;=\u0026thinsp;0.74) and bat (Protest R\u0026thinsp;=\u0026thinsp;0.19, p\u0026thinsp;=\u0026thinsp;0.843) community composition, indicating an absence of spatial autocorrelation. According to the multivariate dispersion analysis based on urban landscape variables and sampling locations of urban bird assemblages, landscape heterogeneity was significantly higher in sampling sites located in UHIs than those in UCIs (F\u0026thinsp;=\u0026thinsp;14.768, prand\u0026thinsp;\u0026lt;\u0026thinsp;0.001). For bats, heterogeneity was also higher in UHIs, but the difference was not statistically significant compared to UCIs (F\u0026thinsp;=\u0026thinsp;3.1466, prand\u0026thinsp;=\u0026thinsp;0.088). Regarding the sensitivity analysis, the lack of significant differences in landscape heterogeneity between UHIs and UCIs for bats appears to be due to small sample size, as our simulations indicated that significance would be reached with at least 65 urban points, whereas for birds it would be reached with 45. The exploration to beta-diversity, through dbRDA ordination (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), revealed bird functional space within UHIs wider than within UCIs.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Effect of urban landscape variables in bird and bat functional traits\u003c/h2\u003e\u003cp\u003eBird species traits did not significantly influence their distribution in line with urban landscape variables (likelihood ratio: deviance\u0026thinsp;=\u0026thinsp;717.7, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.091). In contrast, bat species\u0026rsquo; traits influenced their distribution according to urban landscape variables (likelihood ratio: deviance\u0026thinsp;=\u0026thinsp;275.8, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The fourth-corner analysis revealed a negative association between the presence of underground maternity roosts and the distance to natural and semi-natural areas, as well as between having Hemiptera as the main prey and the distance to permanent water bodies. Conversely, a strong positive association was found between vegetation cover density and having Lepidoptera as the main prey. Regarding echolocation traits, call duration was negatively associated with vegetation cover density (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Effect of urbanisation on functional alpha-diversity\u003c/h2\u003e\u003cp\u003eRegarding functional alpha-diversity, Functional Richness (FRic) was greater in UCIs than in UHIs for both birds and bats. In contrast, Mean Functional Distance (MFD) was higher in UHIs for bats, although this difference was significant between urban site types only when using the standardised measure (Supporting Information A, Fig.\u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), whereas birds showed the opposite pattern. Functional Redundancy (FRed) was higher in UHIs for both urban assemblages (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u0026amp; Supporting Information A, Fig.\u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). As the standardised effect sizes of all functional alpha-diversity metrics mirrored the patterns of the observed values, we focus hereafter on the observed metrics. The only exception is bat MFD, which showed no significant effect in the observed data, but whose SES revealed a significant effect of the type of urban point, with higher values in UHIs than in UCIs (estimate\u0026thinsp;=\u0026thinsp;0.8229\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2105, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.91, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.91 \u0026times; 10⁻⁴) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u0026amp; Supporting Information A, Fig.\u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), which showed the same pattern but significant (Supporting Information A, Fig.\u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFor birds, FRic was significantly negatively correlated with the \u0026ldquo;Rate of Artificialisation\u0026rdquo; (PC1) while MFD displayed significant positive correlations. FRed in birds showed also a significant positive correlation. For bats, FRic was significantly negatively correlated with PC1, while MFD a negative but non-significant correlation. However, its standardised effect size was shown to be significantly negative (Supporting Information A, Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Bat\u0026rsquo;s FRed was significantly positively correlated. Regarding \u0026ldquo;Landscape Configuration\u0026rdquo; (PC2), the only significant relationship detected was a positive correlation with bird FRic. (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e; Supporting Information A, Fig.S3). According to the GLM results (Supporting Information B, Table S3A), birds\u0026rsquo; FRed were influenced by the type of urban site, whereas FRic was associated with PC2 and MFD with PC1. In the case of bats, functional alpha-diversity metrics were only influenced by the type of urban point (UHI or UCI), rather than by PC1 or PC2.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.4. Contribution of functional rarity to bird and bat urban functional diversity\u003c/h2\u003e\u003cp\u003eIn the case of correlations with functional rarity metrics, Functional Distinctiveness (FDi) showed a significant, positive and important correlation with PC1 for birds (R\u0026thinsp;=\u0026thinsp;0.33). In the case of bats, the correlation was significant, negative and moderate (R = -0.17). (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). In line, FDi showed significant differences between UHIs and UCIs in bats but not for birds (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The Functional Scarcity (FSi) of birds and bats showed a positive and significant correlation with PC1 but with a weak signal (R\u0026thinsp;\u0026lt;\u0026thinsp;0.1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) and did not differ between UHIs and UCIs (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) (Supporting Information B, Table S3A). Besides, concerning PC2, all correlations were significant but not important (not shown). Further details about FDi and FSi of each of the species forming urban assemblages is available at Supporting Information B, Table S4.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAccording to Kruskal\u0026ndash;Wallis and Dunn tests, in birds, the loss of the 10% most distinctive species significantly affected FRic, MFD, and FRed, whereas the loss of the 10% scarcest species significantly impacted only MFD. In contrast, for bats, the loss of either the most distinctive or the scarcest species had no significant effect on any functional diversity metric (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e \u0026amp; Supporting Information B, Table S5).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.5. Bird and bat urban functional traits between UHIs and UCIs and along an artificialisation gradient\u003c/h2\u003e\u003cp\u003eAccording to CWMs, birds\u0026rsquo; functional composition varied mainly with PC1, with communities in more urbanised areas dominated by species with longer wings, greater longevity, wider ranges, and higher temperature affinities. Tarsus length decreased with increasing PC2 and was also influenced by the type of urban point (Supporting Information A, Fig. S5A; Supporting Information B, Table S3B). For bats, call duration increased and peak frequency decreased along PC1, reflecting acoustic adaptations to urban clutter and noise. Traits associated with temperature tolerance and ecological specialisation increased with PC2, indicating that more connected urban landscapes supported thermophilic and specialised species (Supporting Information A, Fig. S5B; Supporting Information B, Table S3B).\u003c/p\u003e\u003cp\u003eFor birds, species associated with forests were more abundant in UCIs, whereas those adapted to human-modified habitats prevailed in UHIs. Herbivores and granivores were slightly more abundant in UHIs, while carnivores and invertivores dominated UCIs. Terrestrial species were more common in UHIs, and insessorial species in UCIs. Differences in migratory status were limited (Supporting Information A, Fig. S6A). For bats, FM/QCF call types and Diptera prey dominated both UHIs and UCIs, though Coleoptera were more frequent in UHIs. Tree roosts prevailed overall, with rock crevices more typical of UHIs. Maternity roosts were mainly in human-made structures, followed by tree roosts across both site types (Supporting Information A, Fig. S6B).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eOur study further confirms that functional traits are powerful tools for understanding how species respond to environmental factors, including urban stressors (Petchey \u0026amp; Gaston \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Our results support the hypothesis that, although birds and bats are both flying vertebrates, their functional responses to urbanisation differ, while some strategies remain conserved within urban heat islands in both groups.\u003c/p\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Different functional responses of urban bird and bat assemblages to strong artificialisation\u003c/h2\u003e\u003cp\u003eAlthough highly urbanised sites, such as UHIs, exhibited higher Mean Functional Distance (MFD) in bird assemblages, this was not accompanied by increased Functional Richness (FRic). This incongruence is not surprising. Abundance-weighted metrics such as MFD are not linearly related to species richness, while trait-space volume metrics like FRic almost always are (de Bello et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). These peculiarities help us understand why functional diversity appeared higher in highly urbanised sites, as UHIs, than in UCIs. Such patterns may be linked to the composition of urban bird assemblages. In our case, Poitiers\u0026rsquo; urban bird community is dominated mainly by Passeriformes, leading to low evolutionary distinctiveness (Querejeta et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In fact, closely related communities have shown to have high trait divergence in several cases, potentially due to ecological opportunity and rapid trait divergence (Losos \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Oliveira Hagen et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This divergence is, indeed, reflected in the functional space, through dbRDA ordination, where UHIs showed a broader ellipse than UCIs, highlighting greater variation in trait composition across sites. Our results echo findings from other studies (Lee et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Oliveira Hagen et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). For instance, Oliveira-Hagen et al. (2017) reported higher avian functional diversity in urban areas than in nearby rural sites, even after controlling for species richness. They attributed this \u0026ldquo;paradox\u0026rdquo; to the habitat heterogeneity offered by urban environments compared to more homogeneous rural landscapes. A similar process seems to operate in our study area: UHIs are more heterogeneous than UCIs. This heterogeneity likely contributes to the higher functional diversity we observed. However, this may be only part of they as our non-significant fourth-corner analysis shows that bird traits\u0026rsquo; distribution is not entirely shaped by urban landscape variables. This suggests that other processes may also be at play. One possibility is the role of distinctive or functionally rare bird species, which appear to increase along the urbanisation gradient. These species may be a key driver of functional diversity in birds, unlike in bats, where such a pattern was not detected.\u003c/p\u003e\u003cp\u003eConcerning bird functional rarity, we can confirm our initial hypothesis as our results indicate that the disappearance of distinctive species would strongly affect functional diversity. This pattern is consistent with previous work showing that rare bird species often contribute disproportionately to the functional structure of assemblages (Leit\u0026atilde;o et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Their loss could, thus, have cascaded consequences and ultimately compromising the long-term provision of ecosystem services. In our study, the distinctive species grey heron (\u003cem\u003eArdea cinerea\u003c/em\u003e) illustrates this point well. As the sole representative of the order Pelecaniformes and one of the few aquatic predators specialised in wetland habitats, it maintains a high share of functional diversity despite its rarity. By contrast, bat assemblages do not exhibit the same pattern as the disappearance of functionally distinctive species appears to have little effect on overall functional diversity. In contrast, functional diversity appears to be shaped mostly by the collective contribution of all species, or by the dominance of abundant generalists such as the common pipistrelle, as we had initially hypothesized. This interpretation is supported by our fourth-corner analysis, which shows that bat functional assemblages in urban areas are strongly structured by landscape variables. Taken together, these results suggest that bats are directly affected by anthropogenic stressors and may, therefore, be more vulnerable to intense urbanisation than birds. Indeed, bird functional diversity is strongly influenced by rare species, which serves as a reminder that their disappearance could have disproportionate impacts on entire assemblages.\u003c/p\u003e\u003cp\u003eBird and bat Functional Redundancy (FRed) increased in highly urbanised sites (UHIs) compared to UCIs. This finding aligns with the idea that urbanisation reduces trait diversity and promotes functional homogenisation, whereby several species fulfil similar functional roles (Palacio et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In our study, this is illustrated by the dominance of generalist traits, such as granivores, which tend to replace more specialised traits, such as insectivores, thereby increasing FRed within UHIs. Generalists can be considered redundant due to their high niche overlap (Palacio et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). While FRed may buffer ecosystems against species loss in the short term, it can also reduce ecosystem resilience in the long term by diminishing functional complementarity. Indeed, some urban bird assemblages have already lost nectivorous pollinators, indicating low FRed for that particular ecological role (Pauw \u0026amp; Louw \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). However, urban areas will never host as many species as natural habitats due to intense human pressures such as buildings, roads, and constant human activity. Moreover, the limited number of microhabitats available within cities constrains the range of ecological niches. Therefore, maintaining both high FRed and substantial MFD in urban bird communities is essential for promoting ecosystem resilience. FRed ensures that key ecological roles are preserved even if some species decline, whereas a high MFD enables communities to retain a broad array of ecological strategies, allowing them to cope with environmental changes and to exploit the full range of available urban habitats. Indeed, in our bird assemblages, we observed that high functional diversity, as measured by MFD, co-occurs with substantial FRed. Indeed, it has been argued that FRed and diversity are not mutually exclusive, as species may be functionally similar in some effect traits while remaining distinct in response traits, thereby maintaining both ecological insurance and niche differentiation (Fischer \u0026amp; de Bello \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Similarly, communities may be able to retain high functional diversity together with redundancy across environmental gradients, suggesting that environmental heterogeneity promotes multiple coexisting strategies that enhance ecosystem resilience (Monge-Gonz\u0026aacute;lez et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Indeed, in our study, UHIs exhibited higher landscape heterogeneity. Overall, our study reveals a complex pattern of both congruence and divergence in bird and bat functional diversity metrics along the urbanisation gradient.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Urban landscape variables influence bat but not bird functional traits\u003c/h2\u003e\u003cp\u003eOur study found no significant associations between urban landscape variables and bird functional traits based on the fourth-corner analysis. This suggests that other factors, such as the presence and influence of functionally rare species, may be driving the observed patterns in urban functional structure. This finding also aligns with a potential environmental filtering process that has already shaped bird colonization before reaching the urban core (Querejeta et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Sol et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In other words, the effect of landscape variables likely occurs along the rural-to-urban gradient, rather than between UCIs and UHIs. In contrast, bat functional traits showed significant associations with urban landscape variables, indicating an ongoing process of functional filtering along the urbanisation gradient, from UCIs to UHIs driven by the higher sensitivity to urban stressors. Among the associations detected, bat species were found to rely more on human-made structures and less on underground locations for roosting as the distance from natural and semi-natural areas increased. This pattern supports the idea that species with greater flexibility in roost-site selection are more successful colonisers of urban environments (Jung \u0026amp; Threlfall \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), highlighting the importance of maintaining and restoring natural roosting and maternity sites to enhance bat species and functional diversity in cities.\u003c/p\u003e\u003cp\u003eThe strongest positive association between landscape and functional traits was observed in bat species that primarily feed on Lepidoptera, which were positively correlated with the density of vegetation cover. Indeed, urban moth communities are highly sensitive to vegetation structure, making this finding ecologically meaningful (Tyler \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2020\u003c/span\u003eh\u0026auml;talo et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In our study, key Lepidoptera-feeding bats, including species from the genera \u003cem\u003eRhinolophus\u003c/em\u003e, \u003cem\u003ePlecotus\u003c/em\u003e, \u003cem\u003eBarbastella\u003c/em\u003e, and \u003cem\u003eMyotis\u003c/em\u003e, were predominantly found in UCIs rather than in UHIs. This suggests that the availability of Lepidoptera, and feeding resources in general, may act as a limiting factor for these species in urban settings. Accordingly, we recommend the implementation of urban green infrastructure that prioritizes native plant species, high-quality natural habitats, and ecological connectivity with surrounding rural and natural areas to promote ecological continuity.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Certain birds and bats functional traits are conserved within UHIs\u003c/h2\u003e\u003cp\u003eOverall, our study has revealed that bird and bat colonisation of highly dense anthropised sites is represented by favouring certain traits over others within UHIs. In the case of birds, Community Weighted Means of Hand-Wing Index or HWI, geographical distribution range, lifespan, Community Specialization Index or CSI and Community Temperature Index or CTI are explained by the PC1, as they all increase exponentially along a gradient with higher values of urbanisation. Birds with higher HWI, indicating more pointed wings and greater dispersal ability, were more conserved in UHIs. This aligns with the idea that strong dispersers tend to have larger geographic ranges and are better equipped to colonise novel or disturbed environments, such as urban areas (Arango et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Claramunt et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Neate-Clegg et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In addition to HWI, species with broad distribution ranges appear to also thrive in the highly urbanised landscape, suggesting that dispersal ability plays a key role in successful urban colonisation. Indeed, bird species found in European urban areas have been shown to exhibit greater dispersal abilities compared to those in more natural habitats (M\u0026oslash;ller \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Thus, dispersal abilities would enable birds, located in UHI to cover large areas and therefore seek resources in sites that are less hostile or competitive than UHI. An alternative explanation is that the observed variation in HWI may arise from differences in foraging modes, including flycatching and aerial insectivory, rather than from dispersal ability per se (Neate-Clegg et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Moreover, the increase in lifespan associated with artificialisation may be related to a decrease in predation pressure at highly artificial sites (E\u0026ouml;tv\u0026ouml;s et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), where birds may have chosen a strategy of living longer in order to learn to exploit urban environments (Neate-Clegg et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Urban areas are warmer than their surroundings because built surfaces absorb and release heat (Aram et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This effect peaks in dense zones such as UHIs. Accordingly, the rise in CTI with urbanisation reflects increasing thermal stress, with thermophilic species dominating the most modified environments (Barnagaud et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Piano et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). At the same time, CWM of tarsus length is higher in UCIs, when comparing to UHIs, and decreases with higher values of PC2. Indeed, birds\u0026rsquo; tarsus lengths are associated with locomotory performance, escape flight ability and, thus, capacity to avoid predators (Amiot et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). One hypothesis would lead us to expect a higher number of predators in less urbanised areas and, thus, more predation pressure (E\u0026ouml;tv\u0026ouml;s et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Therefore, this take-off capacity would lead birds to higher changes of survival within UCIs. However, the smaller tarsus lengths observed in urban passerines, the so-called \u0026ldquo;urban winners\u0026rdquo;, have been linked to the production of lower-quality offspring. This is concerning, as in species such as sparrows, the final tarsus length is typically attained at fledging (Gosler et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). This supports a second hypothesis, that increased urbanisation may reduce offspring quality in highly anthropised sites, potentially triggering a long-term degradation of urban bird communities and increasing the risk of local extinctions. Nonetheless, further observational and experimental research is needed to determine which mechanisms are driving these patterns.\u003c/p\u003e\u003cp\u003eIn relation to bat morphological traits, CWMs of forearm length and body mass were higher within UHIs and their variation was explained by the type of urban point, UHI and UCI. Longer forearm lengths are known to be closely associated to faster flight in open areas (Wood \u0026amp; Cousins \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and, potentially, more dispersal capacity, capacity which was also conserved in more urbanised sites in the case of birds. Indeed, a recent study has shown that certain UK urban bat assemblages were larger than in rural areas, potentially due to the absence of pesticides increasing insect availability (Hughes et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In line with this, higher body mass may also lead to faster flight speed and larger flights which would make foraging activities more efficient (Jung \u0026amp; Threlfall \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and potentially in areas further from urban stressors. In fact, some light-tolerant bat species, such as the common pipistrelle (\u003cem\u003ePipistrellus pipistrellus\u003c/em\u003e) and the common noctule (\u003cem\u003eNyctalus noctula\u003c/em\u003e), are known to forage under city lights while maintaining their roosting sites in rural areas outside towns (Hale et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Mathews et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). At the same time, echolocation is a defining trait in bats, shaping how they perceive and interact with their surroundings (Denzinger \u0026amp; Schnitzler \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Our results highlight call peak frequency and duration as key traits influencing adaptation to highly urbanised sites. Longer calls and lower peak frequencies increased with artificialisation, consistent with studies showing that such signals perform better in noisy, open urban environments (Avila-Flores \u0026amp; Fenton \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Jung \u0026amp; Threlfall \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Wolf et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Lower frequencies reduce masking by high-frequency noise, while longer calls enhance spatial resolution (Bunkley et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Hage et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Conversely, according to fourth-corner results, call durations shortened with denser vegetation, supporting evidence that acoustic clutter promotes shorter, broadband calls (Suarez-Rubio et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Starik \u0026amp; G\u0026ouml;ttert \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Undoubtedly, in strongly urbanised areas such as UHIs, morphological, echolocation, ecological, and thermal traits that increase the fitness and survival of birds and bats are consistently favoured. Yet, whether these traits are also different in surrounding rural areas requires further exploration of rural, peri-urban and urban assemblages. In the case of bats, shifts of activity, especially related to hunting behaviour would help shedding light onto the distribution of functional traits due to human modification.\u003c/p\u003e\u003cp\u003eOverall, we have found not only dissimilarities but also similarities on the functional traits, which confer tolerance and/or vulnerability in birds and bats to urban environments. This leads us to reject our hypothesis in which functional traits that are associated with the colonisation of UHIs and UCIs were different between birds and bats. While the effect on some functional traits is specific from birds, such as more longevity and bigger distribution ranges in strong urbanised sites, and to bats, such as echolocation calls characteristics, several functional characteristics follow the same patterns in both groups. Indeed, higher dispersal capacities in highly dense urbanised sites related with bigger wings, as measured by HWI in birds and forearm lengths in bats is a common advantageous trait to colonize highly urbanised sites. It is, hence, plausible that only bird and bat species with high dispersal capacity can reach and persist in anthropised environments, migrating from rural roosts into cities where competition may be lower due to environmental filtering. However, longer wings because of longer forearms may be associated with a different diet more than to a real adaptation to urban environments. Moreover, higher specialisation and higher thermal tolerance associated with UHIs is another common characteristic related to habitat requirements. In fact, the higher specialization may be associated with higher landscape heterogeneity found in UHIs in comparison to UCIs. Despite species-specific traits, our analyses reveal that community composition along the urbanisation gradient is driven by the filtering of conserved functional traits that shape bird and bat distributions across UHIs and UCIs.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e4.4.Towards multifunctional urban landscapes for conservation\u003c/h2\u003e\u003cp\u003eConservation assessments based solely on assemblage composition or taxonomic diversity risk missing key ecological processes and can therefore lead to suboptimal conservation and urban management decisions (Laureto et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Indeed, our functional approach has revealed key findings that may help enhance biodiversity in urban areas. For instance, our results suggest that bird assemblages are partly structured by functionally rare species, and that their local disappearance would disproportionately erode functional diversity. This implies that conservation efforts for urban birds should explicitly prioritise these functionally rare \u0026lsquo;outliers\u0026rsquo; (Violle et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In our case, this is mainly represented by aquatic predators such as the grey heron, whose distinctive traits and low redundancy make them irreplaceable contributors to ecosystem functioning. Aquatic avian predators are widely known to be scarce in urban environments. Similar patterns have been reported for fish-eating waterbirds in the highly urbanised New York/New Jersey Harbour, where suitable wetland habitats are limited. In that case, a dedicated conservation programme protects nesting islands and associated wetlands, couples habitat restoration with disturbance management, and relies on long-term monitoring to safeguard these top predators within a densely urbanised landscape (Craig et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Ultimately, urban conservation strategies should aim to maintain the ecological functions carried by these trait outliers, notably through wetland protection, improved river habitat connectivity, and targeted management of vulnerable aquatic predator populations. At the same time, our study has shown low abundance of insectivorous birds compared to granivorous within the study area. Indeed, previous studies have shown that enhancing tree diversity and vegetation complexity in urban green spaces can increase insectivory by birds (Schill\u0026eacute; et al. 2025). This measure could also be beneficial to increase the diversity of Lepidoptera-feeding bats in UHIs as insectivorous bats are known to respond positively to structurally complex vegetation and abundant insects near water bodies (Suarez-Rubio et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Straka et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Moreover, promoting high-quality insect communities within urban green-blue infrastructures has been identified as a key measure for conserving insectivorous predators (Mata et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Together, these patterns highlight that increasing native vegetation diversity, reducing light and chemical pollution, restoring ecological continuity, and improving wetland and riparian habitats are essential steps to sustain insectivorous birds and bats. Finally, integrating functional traits into the design and management of multifunctional urban spaces could help support low-dispersal bird and bat species in UHIs and other highly urbanised areas. By increasing the local availability of food and nesting resources in these dense urban patches, species with limited dispersal capacity may be able to colonise and persist in sites that are currently beyond their reach. Studies of multifunctional urban green\u0026ndash;blue infrastructure demonstrate how explicit design, implementation and management of multiple ecosystem services can support urban biodiversity (Cook et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Vierikko et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). For example, in the GREEN SURGE Urban Learning Labs, pilot green\u0026ndash;blue projects combining vegetation and water features provided habitat together with social and climatic benefits, confirming that biodiversity-friendly multifunctionality is achievable. Such conservation solutions need inter- and transdisciplinary research that effectively connects ecological knowledge with urban planning and decision-making.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eT\u003c/strong\u003ehis work was funded by Grand Poitiers Communauté Urbaine, the Nouvelle Aquitaine Region, the University of Poitiers as well as RURALITES and EBI Laboratories. We also thank the Agence Nationale de la Recherche (Grant No. ANR-21-CE32-0002-01 [RECODE] to N.B.), the Office Français de la Biodiversité, the intramural Funds from the University of Poitiers (UP-Squared: \u003cem\u003eINOVIE\u003c/em\u003e and ERI: \u003cem\u003eONE CITY\u003c/em\u003e), the European Regional Development Fund (FEDER), the Chaire Biodiversité of the University of Poitiers and finally, the intramural Funds from the French National Centre for Scientific Research (CNRS).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSophie Beltran-Bech and Nicolas Bech obtained the funding.Marina Querejeta, Elie Morin, Nicolas Bech and Sophie Beltran-Bech contributed to the study conception and design. Simon Chapenoire and Alice Chéron carried out the sampling. Marina Querejeta analysed the data. Marina Querejeta, Elie Morin, Nicolas Bech and Sophie Beltran-Bech contributed to the interpretation of results. Marina Querejeta led the writing of the manuscript. All authors contributed critically to the drafts and gave final approval for publication. All authors take responsibility for the work’s integrity and will address any issues concerning its accuracy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaw data has been deposited in \u003cem\u003efigshare\u003c/em\u003e: https://figshare.com/s/ee685a6c019f2024513a\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAmiot C, Harmange C, Ji W (2022) Morphological differences along a chronological gradient of urbanisation in an endemic insectivorous bird of New Zealand. Urban Ecosyst 25(2):465\u0026ndash;475. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11252-021-01156-w\u003c/span\u003e\u003cspan address=\"10.1007/s11252-021-01156-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAncillotto L, Bosso L, Salinas-Ramos VB, Russo D (2019) The importance of ponds for the conservation of bats in urban landscapes. Landsc Urban Plann 190:103607. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.landurbplan.2019.103607\u003c/span\u003e\u003cspan address=\"10.1016/j.landurbplan.2019.103607\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAncillotto L, Tomassini A, Russo D (2015) The fancy city life: Kuhl\u0026rsquo;s pipistrelle, Pipistrellus kuhlii, benefits from urbanisation. Wildl Res 42(7):598\u0026ndash;606. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1071/WR15003\u003c/span\u003e\u003cspan address=\"10.1071/WR15003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAram F, Higueras Garc\u0026iacute;a E, Solgi E, Mansournia S (2019) Urban green space cooling effect in cities. Heliyon 5(4):e01339. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.heliyon.2019.e01339\u003c/span\u003e\u003cspan address=\"10.1016/j.heliyon.2019.e01339\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eArango A, Pinto-Ledezma J, Rojas-Soto O, Lindsay AM, Mendenhall CD, Villalobos F (2022) Hand-Wing Index as a surrogate for dispersal ability: the case of the Emberizoidea (Aves: Passeriformes) radiation. Biol J Linn Soc 137. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/biolinnean/blac071\u003c/span\u003e\u003cspan address=\"10.1093/biolinnean/blac071\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAronson MFJ, Sorte L, Nilon FA, Katti CH, Goddard M, Lepczyk MA, Warren CA, Williams PS, Cilliers NSG, Clarkson S, Dobbs B, Dolan C, Hedblom R, Klotz M, Kooijmans S, K\u0026uuml;hn JL, MacGregor-Fors I, McDonnell I, M\u0026ouml;rtberg M, Winter U (2014) M. A global analysis of the impacts of urbanization on bird and plant diversity reveals key anthropogenic drivers. \u003cem\u003eProceedings of the Royal Society B: Biological Sciences\u003c/em\u003e, \u003cem\u003e281\u003c/em\u003e(1780), 20133330. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1098/rspb.2013.3330\u003c/span\u003e\u003cspan address=\"10.1098/rspb.2013.3330\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAvila-Flores R, Fenton MB (2005) USE OF SPATIAL FEATURES BY FORAGING INSECTIVOROUS BATS IN A LARGE URBAN LANDSCAPE. J Mammal 86(6):1193\u0026ndash;1204. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1644/04-MAMM-A-085R1.1\u003c/span\u003e\u003cspan address=\"10.1644/04-MAMM-A-085R1.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBarataud M (2020) \u003cem\u003e\u0026Eacute;cologie acoustique des Chiropt\u0026egrave;res d\u0026rsquo;Europe. Identification des esp\u0026egrave;ces, \u0026eacute;tude de leurs habitats et comportements de chasse\u003c/em\u003e (P.; B. M. Mus\u0026eacute;um national d\u0026rsquo;Histoire naturelle (ed.); Fourth)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBarnagaud J-Y, Devictor V, Jiguet F, Barbet-Massin M, Le Viol I, Archaux F (2012) Relating Habitat and Climatic Niches in Birds. PLoS ONE 7(3):e32819. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0032819\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0032819\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBarton K, Barton MK (2015) Package \u0026lsquo;mumin\u0026rsquo;, vol 1. Version, p 439. 18\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBasile M (2022) Rare species disproportionally contribute to functional diversity in managed forests. Sci Rep 12(1):5897. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-022-09624-9\u003c/span\u003e\u003cspan address=\"10.1038/s41598-022-09624-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBriones-Salas M, Medina-Cruz GE, Martin-Regalado CN (2024) Taxonomic, Functional, and Phylogenetic Diversity of Bats in Urban and Suburban Environments in Southern M\u0026eacute;xico. Diversity 16(9):527. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/d16090527\u003c/span\u003e\u003cspan address=\"10.3390/d16090527\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrown LM, Graham CH (2015) Demography, traits and vulnerability to urbanization: can we make generalizations? J Appl Ecol 52(6):1455\u0026ndash;1464. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/1365-2664.12521\u003c/span\u003e\u003cspan address=\"10.1111/1365-2664.12521\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBunkley JP, McClure CJW, Kleist NJ, Francis CD, Barber JR (2015) Anthropogenic noise alters bat activity levels and echolocation calls. Global Ecol Conserv 3:62\u0026ndash;71. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.gecco.2014.11.002\u003c/span\u003e\u003cspan address=\"10.1016/j.gecco.2014.11.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBuron R, Hostetler ME, Andreu M (2022) Urban forest fragments vs residential neighborhoods: Urban habitat preference of migratory birds. Landsc Urban Plann 227:104538. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.landurbplan.2022.104538\u003c/span\u003e\u003cspan address=\"10.1016/j.landurbplan.2022.104538\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCardinale BJ, Duffy JE, Gonzalez A, Hooper DU, Perrings C, Venail P, Narwani A, Mace GM, Tilman D, Wardle DA, Kinzig AP, Daily GC, Loreau M, Grace JB, Larigauderie A, Srivastava DS, Naeem S (2013) Biodiversity loss and its impact on humanity. Nature 486(7401):59\u0026ndash;67. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nature11148\u003c/span\u003e\u003cspan address=\"10.1038/nature11148\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCisneros LM, Fagan ME, Willig MR (2016) Environmental and spatial drivers of taxonomic, functional, and phylogenetic characteristics of bat communities in human-modified landscapes. PeerJ 4:e2551. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://doi.org/10.7717/peerj.2551\u003c/span\u003e\u003cspan address=\"10.7717/peerj.2551\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eClaramunt S, Hong M, Bravo A (2022) The effect of flight efficiency on gap-crossing ability in Amazonian forest birds. Biotropica 54(4):860\u0026ndash;868. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/btp.13109\u003c/span\u003e\u003cspan address=\"10.1111/btp.13109\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCook LM, Good KD, Moretti M, Kremer P, Wadzuk B, Traver R, Smith V (2024) Towards the intentional multifunctionality of urban green infrastructure: a paradox of choice? npj Urban Sustain 4(1):12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s42949-024-00145-0\u003c/span\u003e\u003cspan address=\"10.1038/s42949-024-00145-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCraig EC, Elbin SB, Sparks JP, Curtis PD (2015) Identifying important foraging habitat for colonial waterbirds in an urban estuary: a stable isotope approach. Waterbirds 38(4):330\u0026ndash;338. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1675/063.038.0410\u003c/span\u003e\u003cspan address=\"10.1675/063.038.0410\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Bello F, Carmona CP, Lepš J, Szava-Kovats R, P\u0026auml;rtel M (2016) Functional diversity through the mean trait dissimilarity: resolving shortcomings with existing paradigms and algorithms. Oecologia 180(4):933\u0026ndash;940. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00442-016-3546-0\u003c/span\u003e\u003cspan address=\"10.1007/s00442-016-3546-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDenzinger A, Schnitzler H-U (2013) Bat guilds, a concept to classify the highly diverse foraging and echolocation behaviors of microchiropteran bats. \u003cem\u003eFrontiers in Physiology\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fphys.2013.00164\u003c/span\u003e\u003cspan address=\"10.3389/fphys.2013.00164\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDinno A, Dinno MA (2017) Package \u0026lsquo;dunn. test\u0026rsquo;. CRAN Repos 10:1\u0026ndash;7\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEgert-Berg K, Handel M, Goldshtein A, Eitan O, Borissov I, Yovel Y (2021) Fruit bats adjust their foraging strategies to urban environments to diversify their diet. BMC Biol 19(1):123. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12915-021-01060-x\u003c/span\u003e\u003cspan address=\"10.1186/s12915-021-01060-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eE\u0026ouml;tv\u0026ouml;s CB, Magura T, L\u0026ouml;vei GL (2018) A meta-analysis indicates reduced predation pressure with increasing urbanization. Landsc Urban Plann 180:54\u0026ndash;59. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.landurbplan.2018.08.010\u003c/span\u003e\u003cspan address=\"10.1016/j.landurbplan.2018.08.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFischer FM, de Bello F (2023) On the uniqueness of functional redundancy. Npj Biodivers 2(1):23. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s44185-023-00015-5\u003c/span\u003e\u003cspan address=\"10.1038/s44185-023-00015-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGosler AG, Greenwood JJD, Baker JK, Davidson NC (1998) The field determination of body size and condition in passerines: A report to the British Ringing Committee. Bird Study 45:92\u0026ndash;103\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuett\u0026eacute; A, Ga\u0026uuml;z\u0026egrave;re P, Devictor V, Jiguet F, Godet L (2017) Measuring the synanthropy of species and communities to monitor the effects of urbanization on biodiversity. Ecol Ind 79:139\u0026ndash;154. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ecolind.2017.04.018\u003c/span\u003e\u003cspan address=\"10.1016/j.ecolind.2017.04.018\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHage SR, Jiang T, Berquist SW, Feng J, Metzner W (2013) Ambient noise induces independent shifts in call frequency and amplitude within the Lombard effect in echolocating bats. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e, \u003cem\u003e110\u003c/em\u003e(10), 4063\u0026ndash;4068. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1073/pnas.1211533110\u003c/span\u003e\u003cspan address=\"10.1073/pnas.1211533110\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHale JD, Fairbrass AJ, Matthews TJ, Sadler JP (2012) Habitat Composition and Connectivity Predicts Bat Presence and Activity at Foraging Sites in a Large UK Conurbation. PLoS ONE 7(3):e33300. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0033300\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0033300\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHartig F (2022) \u003cem\u003eDHARMa: residual diagnostics for hierarchical (multi-level/mixed) regression models. R package\u003c/em\u003e (version 0.4. 6.)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHughes M, Brown SK, Foster-Plume D, Lee D, Redfern T, Maddock S, Young CH (2024) Big city bats: Species-specific effects of the urban matrix on forearm length and fat stores of bats in the West Midlands, United Kingdom (Chiroptera: Vespertilionidae). Lynx New Ser 54(1):75\u0026ndash;82. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.37520/lynx.2023.005\u003c/span\u003e\u003cspan address=\"10.37520/lynx.2023.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJame A, Noizat C, Morin E, Paulhac H, Guinard Y, Rodier T, Michenaud R, Pigeault R, Yengu\u0026eacute; J-L, Preux T, Royoux D, Beltran-Bech S, Bech N (2024) A combination of methods for mapping heat and cool areas in past and current urban landscapes of Poitiers (France). Ecol Ind 167:112712. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ecolind.2024.112712\u003c/span\u003e\u003cspan address=\"10.1016/j.ecolind.2024.112712\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJohnson MTJ, Munshi-South J (2017) Evolution of life in urban environments. Science 358(6363). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1126/science.aam8327\u003c/span\u003e\u003cspan address=\"10.1126/science.aam8327\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJung K, Threlfall CG (2016) Urbanisation and Its Effects on Bats\u0026mdash;A Global Meta-Analysis. In \u003cem\u003eBats in the Anthropocene: Conservation of Bats in a Changing World\u003c/em\u003e (pp. 13\u0026ndash;33). Springer International Publishing. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-3-319-25220-9_2\u003c/span\u003e\u003cspan address=\"10.1007/978-3-319-25220-9_2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJung K, Threlfall CG (2018) Trait-dependent tolerance of bats to urbanization: a global meta-analysis. \u003cem\u003eProceedings of the Royal Society B: Biological Sciences\u003c/em\u003e, \u003cem\u003e285\u003c/em\u003e(1885), 20181222. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1098/rspb.2018.1222\u003c/span\u003e\u003cspan address=\"10.1098/rspb.2018.1222\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKark S, Iwaniuk A, Schalimtzek A, Banker E (2007) Living in the city: can anyone become an \u0026lsquo;urban exploiter\u0026rsquo;\u0026rsquo;?\u0026rsquo;. J Biogeogr 34(4):638\u0026ndash;651. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1365-2699.2006.01638.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-2699.2006.01638.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKassambara A (2023) \u003cem\u003eggpubr: ggplot2 Based Publication Ready Plots. R package\u003c/em\u003e (version 0.6.0)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKembel SW, Cowan PD, Helmus MR, Cornwell WK, Morlon H, Ackerly DD, Blomberg SP, Webb CO (2010) Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26(11):1463\u0026ndash;1464. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bioinformatics/btq166\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btq166\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKondratyeva A, Knapp S, Durka W, K\u0026uuml;hn I, Vallet J, Machon N, Martin G, Motard E, Grandcolas P, Pavoine S (2020) Urbanization Effects on Biodiversity Revealed by a Two-Scale Analysis of Species Functional Uniqueness vs. Redundancy. \u003cem\u003eFrontiers in Ecology and Evolution\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fevo.2020.00073\u003c/span\u003e\u003cspan address=\"10.3389/fevo.2020.00073\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLaureto LMO, Cianciaruso MV, Samia DSM (2015) Functional diversity: an overview of its history and applicability. Natureza Conserva\u0026ccedil;\u0026atilde;o 13(2):112\u0026ndash;116. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ncon.2015.11.001\u003c/span\u003e\u003cspan address=\"10.1016/j.ncon.2015.11.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee ATK, Ottosson U, Jackson C, Shema S, Reynolds C (2021) Urban areas have lower species richness, but maintain functional diversity: insights from the African Bird Atlas Project. Ostrich 92(1):1\u0026ndash;15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2989/00306525.2021.1902876\u003c/span\u003e\u003cspan address=\"10.2989/00306525.2021.1902876\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLeit\u0026atilde;o RP, Zuanon J, Vill\u0026eacute;ger S, Williams SE, Baraloto C, Fortunel C, Mendon\u0026ccedil;a FP, Mouillot D (2016) Rare species contribute disproportionately to the functional structure of species assemblages. \u003cem\u003eProceedings of the Royal Society B: Biological Sciences\u003c/em\u003e, \u003cem\u003e283\u003c/em\u003e(1828), 20160084. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1098/rspb.2016.0084\u003c/span\u003e\u003cspan address=\"10.1098/rspb.2016.0084\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi M, Cao Y, Dai J, Song J, Liang M (2025) A Comprehensive Review of Urban Expansion and Its Driving Factors. Land 14(8):1534. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/land14081534\u003c/span\u003e\u003cspan address=\"10.3390/land14081534\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiker A, Papp Z, B\u0026oacute;kony V, Lendvai AZ (2008) Lean birds in the city: body size and condition of house sparrows along the urbanization gradient. J Anim Ecol 77(4):789\u0026ndash;795. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1365-2656.2008.01402.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-2656.2008.01402.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLin L, Liu Y, Lin H, Kang B (2024) Considering species functional and phylogenetic rarity in the conservation of fish biodiversity. Divers Distrib 30(3):e13804. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/ddi.13804\u003c/span\u003e\u003cspan address=\"10.1111/ddi.13804\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLosos JB (2008) Phylogenetic niche conservatism, phylogenetic signal and the relationship between phylogenetic relatedness and ecological similarity among species. Ecol Lett 11(10):995\u0026ndash;1003. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1461-0248.2008.01229.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1461-0248.2008.01229.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMagneville C, Loiseau N, Albouy C, Casajus N, Claverie T, Escalas A, Leprieur F, Maire E, Mouillot D, Vill\u0026eacute;ger S (2022) mFD: an R package to compute and illustrate the multiple facets of functional diversity. Ecography 2022(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/ecog.05904\u003c/span\u003e\u003cspan address=\"10.1111/ecog.05904\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMata L, Threlfall CG, Williams NS, Hahs AK, Malipatil M, Stork NE, Livesley SJ (2017) Conserving herbivorous and predatory insects in urban green spaces. Sci Rep 7(1):40970. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/srep40970\u003c/span\u003e\u003cspan address=\"10.1038/srep40970\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMathews F, Roche N, Aughney T, Jones N, Day J, Baker J, Langton S (2015) Barriers and benefits: implications of artificial night-lighting for the distribution of common bats in Britain and Ireland. Philosophical Trans Royal Soc B: Biol Sci 370(1667):20140124. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1098/rstb.2014.0124\u003c/span\u003e\u003cspan address=\"10.1098/rstb.2014.0124\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeill\u0026egrave;re A, Brischoux F, Parenteau C, Angelier F (2015) Influence of urbanization on body size, condition, and physiology in an urban exploiter: a multi-component approach. PLoS ONE 10(8):e0135685. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0135685\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0135685\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMimet A, Kerbiriou C, Simon L, Julien J-F, Raymond R (2020) Contribution of private gardens to habitat availability, connectivity and conservation of the common pipistrelle in Paris. Landsc Urban Plann 193:103671. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.landurbplan.2019.103671\u003c/span\u003e\u003cspan address=\"10.1016/j.landurbplan.2019.103671\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eM\u0026oslash;ller AP (2009) Successful city dwellers: a comparative study of the ecological characteristics of urban birds in the Western Palearctic. Oecologia 159(4):849\u0026ndash;858. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00442-008-1259-8\u003c/span\u003e\u003cspan address=\"10.1007/s00442-008-1259-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMonge-Gonz\u0026aacute;lez ML, Guerrero-Ram\\\u0026rsquo;\\irez N, Kr\u0026ouml;mer T, Kreft H, Craven D (2021) Functional diversity and redundancy of tropical forests shift with elevation and forest-use intensity. J Appl Ecol 58(9):1827\u0026ndash;1837. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/1365-2664.13955\u003c/span\u003e\u003cspan address=\"10.1111/1365-2664.13955\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNeate-Clegg MHC, Tonelli BA, Youngflesh C, Wu JX, Montgomery GA, Şekercioğlu \u0026Ccedil;H, Tingley MW (2023) Traits shaping urban tolerance in birds differ around the world. Curr Biol 33(9):1677\u0026ndash;1688e6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.cub.2023.03.024\u003c/span\u003e\u003cspan address=\"10.1016/j.cub.2023.03.024\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O\u0026rsquo;hara RB, Simpson GL, Solymos P, Stevens MHH, Wagner H (2013) \u0026amp; others. Package \u0026lsquo;vegan.\u0026rsquo; \u003cem\u003eCommunity Ecology Package, Version\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(9), 1\u0026ndash;295\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOliveira Hagen E, Hagen O, Ib\u0026aacute;\u0026ntilde;ez-\u0026Aacute;lamo JD, Petchey OL, Evans KL (2017) Impacts of Urban Areas and Their Characteristics on Avian Functional Diversity. \u003cem\u003eFrontiers in Ecology and Evolution\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fevo.2017.00084\u003c/span\u003e\u003cspan address=\"10.3389/fevo.2017.00084\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePalacio FX, Iba\u0026ntilde;ez LM, Maragliano RE, Montalti D (2018) Urbanization as a driver of taxonomic, functional, and phylogenetic diversity losses in bird communities. Can J Zool 96(10):1114\u0026ndash;1121. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1139/cjz-2018-0008\u003c/span\u003e\u003cspan address=\"10.1139/cjz-2018-0008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePauw A, Louw K (2012) Urbanization drives a reduction in functional diversity in a guild of nectar-feeding birds. Ecol Soc 17(2). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.5751/ES-04758-170227\u003c/span\u003e\u003cspan address=\"10.5751/ES-04758-170227\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePetchey OL, Gaston KJ (2002) Extinction and the loss of functional diversity. \u003cem\u003eProceedings of the Royal Society of London. Series B: Biological Sciences\u003c/em\u003e, \u003cem\u003e269\u003c/em\u003e(1501), 1721\u0026ndash;1727. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1098/rspb.2002.2073\u003c/span\u003e\u003cspan address=\"10.1098/rspb.2002.2073\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePiano E, De Wolf K, Bona F, Bonte D, Bowler DE, Isaia M, Lens L, Merckx T, Mertens D, Van Kerckvoorde M (2017) \u0026amp; others. Urbanization drives community shifts towards thermophilic and dispersive species at local and landscape scales. \u003cem\u003eGlobal Change Biology\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(7), 2554\u0026ndash;2564. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/gcb.13606\u003c/span\u003e\u003cspan address=\"10.1111/gcb.13606\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQuerejeta M, Jame A, Morin E, Chapenoire S, Ch\u0026eacute;ron A, Paulhac H, Ramdani MS, Guinard Y, Preux T, Michenaud R, Yengu\u0026eacute; J-L, Royoux D, Rodier T, Bech N, Beltran-Bech S (2025) Should I Stay or Should I Go: How Urban Heat Gradients Affect the Local Distribution of Birds and Bats. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.2139/ssrn.5206711\u003c/span\u003e\u003cspan address=\"10.2139/ssrn.5206711\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eR Core Team (2024) \u003cem\u003eR: A language and environment for statistical computing.\u003c/em\u003e (Version 4.4. 1). R foundation for statistical computing., Vienna\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRusso D, Ancillotto L (2015) Sensitivity of bats to urbanization: a review. Mammalian Biology 80(3):205\u0026ndash;212. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.mambio.2014.10.003\u003c/span\u003e\u003cspan address=\"10.1016/j.mambio.2014.10.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchille L, Paquette A, Marcotte G, Ouellet H, Cobus S, Barbaro L, Castagneyrol B (2025) Urban tree diversity fosters bird insectivory despite a loss in bird diversity with urbanization. Landsc Urban Plann 256:105274. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.landurbplan.2024.105274\u003c/span\u003e\u003cspan address=\"10.1016/j.landurbplan.2024.105274\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSol D, Bartomeus I, Gonz\u0026aacute;lez-Lagos C, Pavoine S (2017) Urbanisation and the loss of phylogenetic diversity in birds. Ecol Lett 20(6):721\u0026ndash;729. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/ele.12769\u003c/span\u003e\u003cspan address=\"10.1111/ele.12769\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSol D, Gonz\u0026aacute;lez-Lagos C, Moreira D, Maspons J, Lapiedra O (2014) Urbanisation tolerance and the loss of avian diversity. Ecol Lett 17(8):942\u0026ndash;950. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/ele.12297\u003c/span\u003e\u003cspan address=\"10.1111/ele.12297\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSol D, Trisos C, M\u0026uacute;rria C, Jeliazkov A, Gonz\u0026aacute;lez-Lagos C, Pigot AL, Ricotta C, Swan CM, Tobias JA, Pavoine S (2020) The worldwide impact of urbanisation on avian functional diversity. Ecol Lett 23(6):962\u0026ndash;972. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/ele.13495\u003c/span\u003e\u003cspan address=\"10.1111/ele.13495\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStarik N, G\u0026ouml;ttert T (2022) Bats adjust echolocation and social call design as a response to urban environments. \u003cem\u003eFrontiers in Ecology and Evolution\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fevo.2022.939408\u003c/span\u003e\u003cspan address=\"10.3389/fevo.2022.939408\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStraka TM, Lentini PE, Lumsden LF, Buchholz S, Wintle BA, van der Ree R (2020) Clean and green urban water bodies benefit nocturnal flying insects and their predators, insectivorous bats. Sustainability 12(7):2634. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/su12072634\u003c/span\u003e\u003cspan address=\"10.3390/su12072634\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSuarez-Rubio M, Ille C, Bruckner A (2018) Insectivorous bats respond to vegetation complexity in urban green spaces. Ecol Evol 8(6):3240\u0026ndash;3253. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ece3.3897\u003c/span\u003e\u003cspan address=\"10.1002/ece3.3897\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTeeling EC, Springer MS, Madsen O, Bates P, O\u0026rsquo;Brien SJ, Murphy WJ (2005) A molecular phylogeny for bats illuminates biogeography and the fossil record. Science 307:580\u0026ndash;584. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1126/science.1105113\u003c/span\u003e\u003cspan address=\"10.1126/science.1105113\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTiago P, Leal AI, Silva CM (2024) Assessing ecological gains: A review of How arthropods, bats and birds benefit from green roofs and walls. Environments 11(4):76. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/environments11040076\u003c/span\u003e\u003cspan address=\"10.3390/environments11040076\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTyler T (2020) Relationship between moth (night active Lepidoptera) diversity and vegetation characteristics in southern Sweden. J Insect Conserv 24(6):1005\u0026ndash;1015. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-020-00270-y\u003c/span\u003e\u003cspan address=\"10.1007/s10841-020-00270-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUnited Nations, \u0026amp; Department of Economic and Social Affairs (2019) \u003cem\u003eWorld Population Prospects 2019\u003c/em\u003e. United Nations. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://population.un.org/wpp/\u003c/span\u003e\u003cspan address=\"https://population.un.org/wpp/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eV\u0026auml;h\u0026auml;talo AV, Pulli A, Kulmala T, Marin R, Haimi J (2024) Urbanization related changes in lepidopteran community. Urban Ecosyst 27(2):377\u0026ndash;386. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11252-023-01456-3\u003c/span\u003e\u003cspan address=\"10.1007/s11252-023-01456-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVierikko K, Niemela J, Buizer IM, Elands BHM (2014) Green Infrastructure and Urban Biodiversity for Sustainable Urban Development and the Green Economy (GREEN SURGE)\u0026ndash;Is there place for biocultural diversity in the cities? In \u003cem\u003eProceedings of the 7th Annual ESP Conference 2014: Local action for the common good\u003c/em\u003e (pp. 32\u0026ndash;32)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eViolle C, Thuiller W, Mouquet N, Munoz F, Kraft NJB, Cadotte MW, Livingstone SW, Mouillot D (2017) Functional rarity: the ecology of outliers. Trends Ecol \\\u0026amp; Evol 32(5):356\u0026ndash;367\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang Y, Naumann U, Wright S, Eddelbuettel D, Warton D (2017) mvabund: Statistical methods for analysing multivariate abundance data. R Package Version, \u003cem\u003e3\u003c/em\u003e(3)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWickham H, Averick M, Bryan J, Chang W, McGowan LD, Fran\u0026ccedil;ois R, Grolemund G, Hayes A, Henry L, Hester J (2019) \u0026amp; others. Welcome to the Tidyverse. \u003cem\u003eJournal of Open Source Software\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(43), 1686\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWickham H, Fran\u0026ccedil;ois R, Henry L, M\u0026uuml;ller K (2021) \u003cem\u003edplyr: A Grammar of Data Manipulation. R package version 1.0.5.\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWolf JM, Jeschke JM, Voigt CC, Itescu Y (2022) Urban affinity and its associated traits: A global analysis of bats. Glob Change Biol 28(19):5667\u0026ndash;5682. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/gcb.16320\u003c/span\u003e\u003cspan address=\"10.1111/gcb.16320\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWood H, Cousins SAO (2023) Variability in bat morphology is influenced by temperature and forest cover and their interactions. Ecol Evol 13(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ece3.9695\u003c/span\u003e\u003cspan address=\"10.1002/ece3.9695\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZabala-Forero F, Cortes-Gomez AM, Urbina-Cardona N (2025) How low-abundance amphibians shape functional diversity across tropical forest succession stages? Ecol Ind 171:113140. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ecolind.2025.113140\u003c/span\u003e\u003cspan address=\"10.1016/j.ecolind.2025.113140\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"biodiversity-and-conservation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bioc","sideBox":"Learn more about [Biodiversity and Conservation](https://www.springer.com/journal/10531)","snPcode":"10531","submissionUrl":"https://submission.nature.com/new-submission/10531/3","title":"Biodiversity and Conservation","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"urbanisation, birds, bats, functional diversity, functional rarity","lastPublishedDoi":"10.21203/rs.3.rs-8172612/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8172612/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUrbanisation is a major driver of global biodiversity loss, including functional biodiversity. This study characterises the functional space of urban bird and bat assemblages in the city of Poitiers, France. Specifically, our objectives were to quantify functional diversity across Urban Heat and Cool Islands, test the role of rare species, identify traits linked to urban tolerance or sensitivity, and examine whether birds and bats share ecological strategies in response to urban stressors. Bird and bat assemblages were sampled across UHIs and UCIs within Poitiers. Functional traits were compiled for each species, and relationships with fine-scale urban landscape variables were assessed using fourth-corner analysis. We quantified functional diversity metrics (alpha, rarity, beta) and trait distributions using Community Weighted Means. Birds and bats exhibited contrasting functional responses to urbanisation. In birds, functional alpha-diversity was higher in UHIs than in UCIs, driven mainly by functional rarity rather than local habitat variables. In contrast, bat functional diversity decreased in UHIs, with no detectable contribution of rare species but a strong influence of urban landscape structure. Urban tolerance was associated with high dispersal and longevity in birds, and with larger size and clutter-adapted echolocation in bats. Both groups shared key ecological adaptations to urbanisation which likely enables persistence in densely urbanised environments. Overall, urbanisation acts as a strong ecological filter, but its influence differs across taxa. This study confirms once again that functional approaches reveal hidden information in taxonomic-only approaches which reveal essential information for urban landscape managing and conservation.\u003c/p\u003e","manuscriptTitle":"Traits and the City: functional trait space in urban bird and bat assemblages","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-04 17:51:26","doi":"10.21203/rs.3.rs-8172612/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-03T09:12:56+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-02T10:36:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-25T08:23:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"306468678144645630314445594648167327883","date":"2025-12-05T14:52:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"234225366920613624397422734031184400008","date":"2025-12-03T03:24:22+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-02T15:07:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-02T13:31:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-25T07:14:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"Biodiversity and Conservation","date":"2025-11-21T10:22:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"biodiversity-and-conservation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bioc","sideBox":"Learn more about [Biodiversity and Conservation](https://www.springer.com/journal/10531)","snPcode":"10531","submissionUrl":"https://submission.nature.com/new-submission/10531/3","title":"Biodiversity and Conservation","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"69ef17b7-c52e-427f-a85b-75736bb4443c","owner":[],"postedDate":"December 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T16:23:48+00:00","versionOfRecord":{"articleIdentity":"rs-8172612","link":"https://doi.org/10.1007/s10531-026-03318-8","journal":{"identity":"biodiversity-and-conservation","isVorOnly":false,"title":"Biodiversity and Conservation"},"publishedOn":"2026-03-23 16:09:24","publishedOnDateReadable":"March 23rd, 2026"},"versionCreatedAt":"2025-12-04 17:51:26","video":"","vorDoi":"10.1007/s10531-026-03318-8","vorDoiUrl":"https://doi.org/10.1007/s10531-026-03318-8","workflowStages":[]},"version":"v1","identity":"rs-8172612","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8172612","identity":"rs-8172612","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}