Testing barrier leaking and negative connectivity in biogeographical urban homogenization

Testing barrier leaking and negative connectivity in biogeographical urban homogenization | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Testing barrier leaking and negative connectivity in biogeographical urban homogenization Roberto Zeferino, Aitor Gastón, Miguel Berdugo, Felipe Domínguez Lozano This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7188073/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Homogenization is a process which is particularly relevant in urban environments. We focus on the flora of a large mediterranean Spanish city, Madrid, located along two different edaphic biogeographical regions. We test whether biogeographical homogenization, in terms of anthropogenic biogeographical barrier crossing, has been taking place, and to what extent. Secondly, we attempt to shed light on the relationship between urban connectivity and urban homogenization. We use the public parks system in Madrid to test whether these spaces could foster an unnatural increase in species movements, and therefore a ‘leakage’ in the biogeographical barrier, diluting the barriers among territories and providing increased opportunities for homogenization. Biogeographical homogenization is not consistent in urban Madrid. Our results identify the common and generalist flora as the most significant plant set in terms of diluting the barrier. The biogeographical homogenization caused by specialist flora (calcifuge/calcicole) is asymmetrical, with a ratio of 7.72:1 of calcifuge to calcicole. Our results do not support the assumption that more urban connectivity is related to greater urban homogenization. The biogeographical barrier, together with human mediated dispersal and the microheterogeneity of urban green areas are possible factors that may explain this lack of relationship. Biogeographical barriers in cities continue to play a natural role and homogenization is a differential process resulting in distinct effects depending on plant ecology and biogeography. Although urban spaces are highly altered, they host several groups of floras, and they contribute to biogeographical patterns and processes. Hence, there is still room for biological conservation in cities. Urban biodiversity Urban conservation Urban flora Urban Biogeography Madrid Public parks Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Highlights The use of a comprehensive plant dataset that includes historical records from the 19th century and recent inventory data from the last three years. Common flora dilutes urban biogeographical barriers more effectively. Specialist flora causes asymmetrical biogeographical homogenization. No direct relationship was found between urban connectivity and homogenization. Cities, despite alterations, retain biogeographical patterns and processes. 1. Introduction Biotic homogenization is a process which is highly associated with the Anthropocene (Daru et al. 2021). It has negative consequences (Olden et al. 2004) in ecological (Kinzig et al. 2013), economic (Hanley and Perrings 2019; Edwards and Abivardi 1998) and evolutionary (Moritz 2002) realms. Traditionally, homogenization has been closely associated with the role of non-native species in urban settings (McKinney and Lockwood 1999), as urban habitats are more receptive to non-native species (Pyšek et al. 2010; Roy et al. 1999), which in turn have been responsible for increasing overall species richness (Lososová et al. 2012; McKinney 2008; Wania et al. 2006). Thus, temporal aspect of homogenization is widely acknowledged, and extensive and rapid changes associated with many years of urban planning, including not only housing and ever-increasing daily traffic, but also horticulture and green design, have contributed to the present characteristic turnover of urban species (Husté and Boulinier 2007; Lososová et al. 2016), increasing the presence of nonnative species. However, non-native homogenization is just one particular type of a more participated process. Thus, homogenization can also embrace other fractions of the current urban biota assemblages, reflected not only in the pools of non-native species but also in non-natural assemblages of native species, since urban biodiversity is the result of intermingled species origins (Kowarik 2011; La Sorte et al. 2007; Lundholm and Marlin 2006; McKinney 2002; Padullés Cubino et al. 2019; Palma et al. 2016; Wittig 2004). Recent extinction and colonisation events have contributed to the appearance of new urban native species (Duncan et al. 2011; Hahs et al. 2009; Husté and Boulinier 2007), with some reaching high levels of urban abundance (Blair 1996), characterised by broader niche properties (Palacio 2019; Palacio 2020) and therefore contributing to urban homogenization as well (Blair 1996; Kark et al. 2007). This broader concept of homogenization is not yet considered, and little is known about how natural factors, such as regional or biogeographical scale patterns, may be affected by non-natural movements of the biota in cities (Li et al. 2023; Marchetti et al. 2006). For example, we can expect that the anthropogenic leaking of biogeographical barriers in a city will also contribute to homogenization as species from different biogeographical origins may come to live together. Moreover, this biogeographical homogenization may have different effects according to the origin of the biota, that is, whether they are rare or narrowly distributed, common or widespread, as well as whether they are specialist or generalist or native or non-native. Urban connectivity may play a role in this type of biogeographic homogenization of biota. Connectivity is a spatial trait that depends on distribution and shape of habitat patches (in the case of cities, urban green areas) as well as on species dispersal abilities (Saura and Pascual-Hortal 2007; Taylor et al. 1993). The positive function of connectivity is widely accepted in biodiversity management. Better connectivity promotes dispersion, increases gene flow, and precludes demographic decline (Baguette et al. 2013; Hansson 1991; Lookingbill et al. 2010) while negative effects have rarely been detected (Orrock and Damschen 2005). Thus, regarding homogenization, negative connectivity can be seen as an actor fostering unnatural assemblages of native urban flora due to the breaking down of natural isolation that may occur as urban connectivity increases. This could be of particular concern when we focus on the urban public recreation park network, given the ability of these spaces to support biodiversity (Talal and Santelmann 2019). The biodiversity of public parks is driven by natural factors (mainly climate and regional context) as well as by anthropogenic alterations and in fact species composition in green urban spaces is closely related to management actions (Ibsen et al. 2020; Threlfall et al. 2017). Moreover, studies have shown that in some cases they do not follow natural patterns of species diversity (Alós Ortí et al. 2022). Hence, it is crucial to explore the way in which negative connectivity among urban green spaces may contribute to the crossing of biogeographical barriers in urban settings, resulting in greater urban homogenization. This increased understanding of the current situation could help to improve our ability to manage urban biodiversity with the aim of protecting natural assemblages also in urban scenarios. Madrid is a large European city located in a mediterranean environment. Interestingly, it is situated between two distinct biogeographical regions (Grijalbo Cervantes 2019; Izco 1984; Rivas-Martinez et al. 1987) associated with the parent material of the soils. The city lies on an area of confluence between siliceous sedimentary rocks (mainly arkoses) and carbonate or sulphate rich sedimentary materials (mainly marls and gypsum). The soil types partially explain urban plant diversity (Jogan et al. 2022; Kühn et al. 2004), so in the Madrid case there is a unique opportunity to study the effect of edaphic barriers, since this city is home to two distinct types of edaphic flora. In addition to the abovementioned geological aspect of Madrid, the city has an extensive system of managed green spaces within urban areas, with older public gardens in the downtown area as well as modern green spaces in the suburban areas. Finally, there is a relatively complete knowledge of the distribution of wild plant species within the city limits, thanks to readily available historical work along with a very recent inventory of Madrid flora (Bot Mad et al. 2023; Cutanda 1861; García 1983). Given this interesting context, Madrid provides a suitable scenario for testing several hypotheses related to the link between spatial homogenization types, origin of urban biotas, biogeographical barriers, and connectivity. 1.1. Objectives Our main objective is to test whether biogeographical homogenization has been taking place in an urban environment, and if so, to what extent. Cities may be compatible with the natural process of biogeographical isolation, in which the effect of biogeographical barriers is apparent, or on the contrary, urban processes may in fact dilute the biogeographical barrier. To test these notions, we measure urban biogeographical homogenization across different flora elements. Thus, we analyse the way in which spatial urban homogenization affect: 1) total urban flora, 2) native and non-native groups, 3) common (in opposition to rare) plants and 4) generalist and specialist plants (flora of different lithologic origins). Secondly, we explore urban connectivity in relation to urban homogenization. The extent and location of public parks may encourage an unnatural increase in species movements and colonization thus creating greater opportunities for spatial homogenization. To explore the role of negative connectivity in fostering the dilution of biogeographical barriers with regard to flora in the city of Madrid, we test the hypothesis that areas with increasing connectivity are those where greater spatial homogenization is occurring (in terms of plant overall richness). If this is so, we can expect plant responses to the present connectivity and biogeographical barriers to differ according to both lithological preferences of the species and distribution range (common plants). We study the hypothesis at two levels: first using the whole territory of the Madrid city and secondly selecting only those areas configuring the biogeographical border inside the city. 2 Material and Methods 2.1. Study Area The study area, hereafter referred to as Urban Madrid, coincides with the area considered in the most recently published checklist (Bot Mad et al. 2023). This region covers approximately 36,041 hectares and consists of exclusively urban areas within the city. 3.22 million people live within this area (INE, 2024); 8,934 inhabitants/km 2 . The suburban and natural areas inside the city limits were excluded from the study since these areas lacked distinctive urban characteristics. Hence, areas with less than 1000 inhabitants/km 2 were not taken into consideration, nor were areas in which less than 50% of the area was concrete/asphalt-covered, or parts of the city bordering rural areas (suburban areas) (MacGregor-Fors 2011). Furthermore, we excluded zones on the outskirts of the city with minimal anthropogenic disturbance that retain their natural connectivity with river basins and drainage networks and where significant earthworks have not taken place, such as Monte del Pardo or Pinar de Valdelatas (natural areas) (Fig. 1 ). The most updated Mediterranean biogeographical regionalization for Iberia established six provinces and Madrid city lies between two of them, central and west Mediterranean provinces (Rivas-Martinez, et al. 2017). This border has been acknowledged since early times and is established based on strong lithology differences among floras of both sides (Izco 1984). Biogeographical borders are difficult to set at local scales, and we decided to establish the border line between both provinces for Urban Madrid following current knowledge of the lithology and parent soil origin (extracted from IGME, (Goy Goy et al. 2023). As a result, two city areas for each biogeographical provinces were established, one having soils of a calcifuge nature (henceforth ‘acidic’), covering 24,601 ha and the other, covering 11,440 ha., presenting soils of an alkaline (henceforth ‘basic’) nature. 2.2. Data Plant species presence and abundance data were taken from the Flora and Conservation Database for Urban Madrid (FCDUM, here on, Bot Mad et al. 2023). This database contains over 30,000 records for the city of Madrid, of which 18,700 are within our study area. A total of 1,516 species were considered for Urban Madrid. Spatial data were in two different formats, 1x1 km utms quads and more precise geographical coordinates (GPS precision). FCDUM only considers vascular flora, and both native and non native plants, the latter excluding cultivated and horticultural plants. Native and non native status was based on the criteria of Bot Mad et al. 2023. The urban green areas (UGAs) encompass public parks, forest parks, river spaces, green streets and infrastructures, semi-natural vegetation, and undeveloped plots (UTE Tecnigral-Dasotec 2016). Green buildings, street trees, private gardens, and cemeteries were excluded from this study as they represent less than 0.1% of the total UGAs in Madrid. In accordance with these criteria, a total of 11,494 UGAs were identified, ranging in size from 1 m 2 to over 2.4 km 2 . All cartographic data, species richness and abundance, distribution of UGAs and lithology (extracted from IGME, (Goy Goy et al. 2023) were referenced to a 1x1 km UTM grid for Urban Madrid (159 UTM cells in total). The number of records per species in each cell was used to create a presence/absence of flora matrix per cell. The lithology based on chemical composition was recorded in a binary manner (acidic, for siliceous materials, and basic for carbonate and sulphate materials) for each cell. To perform this transformation, the lithological information was simplified by grouping all types of gypsum and gypsum clays into the 'basic' category and all sandy clays and riverbeds into the 'acidic' category, excluding cells with mixed parent material from the analysis (23 in total). 2.3. Analyses The presence/absence of flora matrix was transformed into a dissimilarity matrix using the Jaccard index, chosen for its effectiveness with binary data (Choi et al. 2010; Chung et al. 2019). This dissimilarity matrix was analysed using a PERMANOVA (Anderson 2017) in order to identify significantly different groups of plants according to the biogeographical areas defined (acidic and basic cells). The analysis was performed using ADONIS (Anderson 2001) to obtain the most significant values. We used a reduced model, as the matrix is not square, and 9,999 permutations were performed (Bakker 2024). In addition, we used dissimilarity matrix values to perform an ordinal analysis based on the Multidimensional Scaling Analysis (NMDS) technique (Kruskal and Hill 1964; Shepard 1962; Shepard and Arabie 1979). We decided to use this type of analysis as it is a commonly used statistical tool in community ecology (Schaefer et al. 2005), conservation (Ruhí et al. 2017), biogeography (Kreft and Jetz 2010) and land management (Dwyer et al. 2019). To obtain groups with a 50% confidence interval, we used the beta-dispersion method (Anderson 2017). We carried out this analysis for three different data sets from FCDUM. Firstly, we took into consideration the total urban vascular flora (1501 species). Secondly, we selected only the common plants, defined as those plants with a number of observations exceeding the 90th percentile (more than 40 records per species) comprising 159 species. Finally, we used the differentiation among native (1279 species) and non-native plants (143 species) for the third analysis. To evaluate whether the edaphic preferences of the plants affect the relationship of the flora with connectivity and biogeographical barriers, the species associated with each parent material (acidic/basic) were identified. To classify the species, a chi-square statistic was used. Species with less than 5 occurrences in the area were not considered in this analysis to ensure the significance of the results and avoid either empty cells or cells with a frequency of less than 5% in the chi-square analysis (Tallarida and Murray 1987). After applying this filter, the database extracted from FCDUM was reduced from 1516 to 501 species. We use the term 'generalists', for plants showing no preference for any parent material, 'calcifuge flora', for plants associated with acidic parent material, and 'calcicole flora', for plants growing on basic substrates. To address our second hypothesis, that urban connectivity affects spatial urban homogenization, we first assessed the role of each UTM cell in the connectivity for plant species. Hence, we selected all the UGAs in Urban Madrid with an area greater than 2,500 m². This size was deemed biologically significant enough to host natural colonization and extinction processes. After applying this filter, we analysed 1,856 out of the total 11,494 UGAs. The Probability of Connectivity (PC) index was calculated as a measure of the overall connectivity of the system (Saura and Pascual-Hortal 2007), i.e., the probability that two randomly selected UGAs are actually connected. The area of each UGA was used as an estimator of the habitat availability and the probability between pairs of UGAs was estimated using Euclidean distances. The contribution of each UGA to overall connectivity was calculated by measuring the relative decrease in PC resulting from the removal of each UGA. We considered a maximum dispersion value of 1050 m, as this may be considered the usual maximum dispersal distance for most flora (Corlett 2009). We considered the flux component of the probability of connectivity (Saura and Rubio 2010) that measures the contribution to connectivity of each UGA when that UGA is the starting or ending patch of each connection between patches. We analysed the relationship between connectivity and biogeographical homogenization using robust regression. This method allows the effect of outliers to be reduced in the regression of the data (Huang et al. 2016). As the dependent variable, we used the decimal logarithm of species records per grid, and as the independent variable, the decimal logarithm of connectivity per cell. For this last analysis we used two approaches, first we studied connectivity-homogenization relationship across the whole study area, Urban Madrid, using the number of common species present. As connectivity values, we calculated the dPCflux index (Saura and Rubio 2010). As a measure of homogenization, we consider the number of common plants per square, assuming that high common species richness denotes higher homogenization. Since the relationship between connectivity and biogeographical homogenization may be mediated by distance to the border and habitat specificity, we also performed a second approach. We assumed that the effect of connectivity onto biogeographical homogenization is gradual, if strong the signal maybe detected in both data set, if weak only around the border and for the most sensitive plants, therefore this second approach. We analysed only the area around the biogeographical border. As a measure of homogenization we took into consideration the number of specialist species from one type of parent material present in cells of the other parent material. Thus, in this case, for homogenization to take place, we would expect a positive correlation among calcicole plants and acidic cells and vice versa, a positive correlation between calcifuge plants and basic cells along the border. We selected cells within the maximum dispersal distance established in our analysis (1050 m) on both sides of the border line, 79 UTM cells in total. In this latter case, we only considered connections between pairs UGAs from different regions. To do so, we used an adaptation of the dPCflux index consisting of considering only the area of the source habitat patches and multiplying it by the probability of connection between the two nodes (without considering the area of the destination patch). On considering those two data sets we take into account both the effect of barrier leaking and the overall plant richness distribution in the city. In both cases, dPCflux values were upscaled from UGAs to 1 km cells using area weighted sums. 3 Results 3.1 Total urban flora Figure 2. NMDS values on its two main axes for the cells of Urban Madrid for the total urban flora. Blue dots show acidic cells, and red dots show basic cells. Ellipses show the 50% confidence interval, using the beta-dispersion method. Taking into consideration the whole urban flora set in the city of Madrid, the PERMANOVA analysis identifies significantly different plant compositions for the two biogeographical areas, basic and acidic (R-square = 0.027, Pseudo-F = 2.959 and p-value = 0.0001). In addition, the NMDS results also differentiate both areas, as shown by the two ellipses produced by the beta-dispersion (Fig. 2). However, this differentiation is not strong, as these two cell groups overlap substantially in Fig. 2., and variance in the NMDS analysis is not high (Stress = 0.221). 39% of species appear on both parent materials. 3.2. Different groups of urban flora Exploring flora subgroups, PERMANOVA results show that differences among regions are statistically significant in all cases (a. common plants: R-square = 0.032, pseudo-F = 3.067 and p-value = 0.0001; b. native plants: R-square = 0.295, pseudo-F = 3.128 and p-value = 0.0001 and c. non-native plants: R-square = 0.024, pseudo-F = 2.125 and p-value = 0.001). However, Fig. 3 again reveals that the UTM groups share a large amount of their respective flora compositions as shown by the overlap of the ellipses and variance values (common plants: Stress = 0.210; native plants: Stress = 0.210; non-native plants = 0.221). The group of common plants seems to be the most affected by homogenization as centroids of the ellipses of the two cell groups are close together (Fig. 3 A). These results suggest that the two biogeographic areas are consistent, they shelter different compositions of flora, considering the urban flora as a whole as well as specific groups, common species, or native and non-native species. However, the NMDS results do not point to strong differences, and we cannot dismiss some homogenization in the urban flora of Madrid. This is specially true when centroids are closer (common and non-native flora are considered). 3.3. Soil parent material preference flora According to parent material plant preferences within the study area, 29 calcifuge species and 48 calcicole species were identified (see Table 1 , supplementary material). Figure 4 shows the urban distribution for both, revealing an asymmetric distribution of specialist flora. This asymmetry is quantitatively evident, as the presence of calcifuge flora is up to 7.72 times greater in the basic area than calcicole flora in the acidic area (see supplementary material). Therefore, considering this differential proportion of edaphic specialist species, the biogeographical barrier has an asymmetrical effect, affecting calcicole flora to a greater extent since calcicole species appear less capable of crossing into acidic areas. In spite of the fact that basic parent material is usually more demanding and stressful for plants, some calcifuge plants are also present in this territory in Urban Madrid. 3.4. Connectivity and homogenization We produced the map of Fig. 5 to show how connectivity is distributed across Madrid UGAs. The map highlights the significance of size and topology in the flux fraction of connectivity. Larger areas tend to exhibit higher dPCflux values. Spatial arrangement also plays a crucial role in determining dPCflux; relatively small UGAs have higher dPCflux values if they are close (see the polygons surrounding the course of the river). If negative connectivity is taking place, we may expect that UGAs with higher dPCflux values in this map (important nodes of connectivity) would be also sites with higher values of common species richness, the group identified as more prone to homogenization. However, according to Fig. 4 , there is no significant relationship between connectivity in UGAs and the richness of common flora in Urban Madrid (p-value of 0.454 after 1000 bootstrap repetitions, applied to the slope coefficient of a robust regression between connectivity and species richness). Thus, in the current UGA system, cells with higher connectivity do not harbour a greater number of common species, therefore they are not homogenization sites. To confirm that the lack of relationship between connectivity and homogenization was consistent across areas and species, we analysed connectivity through the specialist edaphic flora along the biogeographical border line. Thus, we performed two new robust regressions for each type of edaphic specialist present on the other side of the border (Fig. 7 ), one case focusing on calcifuge plants growing in basic cells, and the other on calcicole plants in acidic cells, in both cases considering only the biogeographic border (79 cells in total, 49 for acidic cells and 30 for basic cells). Figure 7 shows no relationship in either case (calcifuge flora on basic parent material, p-value of 0.950; calcicole flora on acidic parent materials, p-value of 0.808). 4 Discussion Biogeographical homogenization is not consistent in urban Madrid. Overall, flora segregation occurs across the biogeographical barrier. Distribution of UGAs and connectivity does not contribute to dilute the effect of the barrier either. However, our results indicate that the response of the flora to homogenization is far from simple, and that urban biogeographic homogenization may be a gradual and differential process, depending on the flora type involved. 4.1. Role of flora groups in contributing to biogeographical homogenization The lack of specialists has been denoted as a major cause for homogenization (Clavel et al. 2011). In fact, this process has been measured in some particular habitats (A specialist-generalist classification of the arable flora and its response to changes in agricultural practices), in our work the specialist group (acidic and calcicole plants) has shown biogeographical segregation, as certain species appear predominantly on acidic parent materials (acidic flora) and others occur on basic (calcicole flora) (as shown by the chi-square analysis). Moreover, the effect of soil ph on plant composition and richness have been widely studied (Pärtel 2002, Crespo-Mendes et al. 2019). There are many examples of soil ph explain plant diversity at local scales (Gough et al. 2000; Schuster and Diekmann 2003; Sebastiá 2004) For Iberian flora, edaphic factors are fundamental to explain biogeography patterns, and it is a clear distinction between acidic and calcicole plant distribution (Buira et al. 2021). Our results show the barrier segregate most for calcicole flora, and there is no biogeographical leaking in this case. These species are adapted to edaphically stressful parent materials and are less commonly found in urban environments (Escudero et al. 2015; Mota et al. 2011). Calcicole flora resulting from edaphic evolutionary selection form highly specialized communities that are much more demanding than calcifuge species. This hyper-specialization makes them poor competitors in highly dynamic urban environments (Evans et al. 2011; Hansson 1991; Mota et al. 2011). However, our results reveal a consistent asymmetric biogeographical homogenization when considering acidic plants. This flora contributes most towards weakening the biogeographical barrier separating the two edaphic areas, given that these species are also found in areas with basic parent material (Fig. 4 ). 413 occurrences of acidic species on basic substrates were recorded compared to 193 occurrences of calcicole plants on acidic substrates (weighted according to the size of each area, the cross-border occurrence of acidic species is 7.72 times that of calcicole species). Acidic flora, despite being specialist species, are not as demanding as calcicole flora, and many of the records correspond to disturbed areas such as road verges and urban wastelands in both biogeographical territories in Urban Madrid. Considering non-native and native flora groups, it is known that they to exhibit different behavioural traits in urban settings (Lososová et al. 2012; Pyšek et al. 2010), just as more abundant flora tend to employ different strategies to rarer flora (Levins 1968; MacGregor-Fors and Schondube 2011; Marvier et al. 2004). Our results show that, in the case of the city of Madrid, there is no distinction between the two different floras based on the two edaphic biogeographical provinces. We observe that both native and non-native flora contribute similarly to biogeographic characterization, with no significant differences in their response to the biogeographic barrier. It seems that in highly dynamic, modified urban environments, the origin of the flora is secondary, while tolerance to changes plays a fundamental role, both in native and non-native species. In accordance with other authors, that have found different rates of homogenization depending on composition and biogeography (Pearse et al. 2018), we also detect differential homogenization according to plant groups or composition, thus common urban species are the most sensible to biogeographical homogenization in our case (centroids in Fig. 3 A). These are mainly ruderal species, with known ability for colonization and resistance to frequent disturbance, while also being widely distributed beyond the studied area (positive correlation between number of UTM cells in urban Madrid and number of UTM cells in whole Iberia for this flora set, data not shown). The characteristics of the urban environment (extreme fragmentation and unpredictable colonization sites) further favour this species group (Evans et al. 2011; MacGregor-Fors and Schondube 2011; Pellissier et al. 2012; Shochat et al. 2006; Williams et al. 2009), which dominate the flora of Urban Madrid. It has been highlighted that common species also tend to be generalist species (Denelle et al. 2020), and in our case this seems to be true, as both biogeographical provinces in Urban Madrid (as delimited by the two groups of edaphic UTMs) share up to 39% of the total species. In addition, we show that of the 501 total species considered in the chi-square analysis, 85% were present in both biogeographical areas of Urban Madrid and therefore are termed generalist species. Some authors have reported similar figures for homogenization (Lososová et al. 2012; Price et al. 2020; Rahel 2000). From an overall perspective the different groups of flora differ in their responses to the biogeographical barrier, making homogenization a gradual and differential process. However, rather than depending on their origin (native or non-native), this difference is more related to their abundance and edaphic preferences. It is the common and generalist flora that contribute most towards diluting the barrier. The biogeographical homogenization caused by specialist flora (acidic/calcicole) is asymmetrical, the ratio of connectivity to calcicole in terms of contribution to the homogenization process being 7.72:1. As for the entire flora, the two areas share a noticeable proportion of the same flora (39%). 4.2. Connectivity and Human-Mediated Dispersal The creation of new UGAs has been linked to an increase in artificial connectivity (Czarnecka et al. 2013; Goddard et al. 2010; Lepczyk et al. 2017). Equally, some authors have also suggested that new UGAs contribute to homogenization (Rahel 2007; Strecker and Brittain 2017; Trentanovi et al. 2013). Our results do not support the assumption that increased urban connectivity necessarily leads to greater urban homogenization. This lack of relationship is evident at two levels of analysis. On the one hand, considering the number of common ruderal generalist plants across Urban Madrid as a whole, we found no relationship to an increase in UGA connectivity per cell (Fig. 6 ). The increase in overall plant richness in cities is closely related to homogenization of this species pool (McKinney 2008; Knapp 2010), but not to connectivity in Urban Madrid. On the other hand, considering only the cells around the border, the increase in asymmetric biogeographical homogenization recorded showed no relationship with the better-connected cells (Fig. 7 ). The most direct explanation for this situation is that the positive effect on the dispersal and colonization processes of a better-connected network does not counteract the natural effect of the biogeographical barrier. Our results suggest that the barrier is still in place. This barrier robustness identifies gypsum and gypsum clays areas and calcicole floras as potential biodiversity reservoirs, and less prone to homogenization and invasion phenomena. Equally important, in urban areas, connectivity tends to be influenced by 'artificial dispersal barriers', not found in natural environments. For example, building height, extension of paved areas (Riley et al. 2014; Robertson et al. 2013), areas with artificial lighting and noise (Hale et al. 2015; Ware et al. 2015), and competition with invasive species (Kennedy et al. 2002; Lockwood and Welbourne 2023; Trentanovi et al. 2013), occur either exclusively or at least to a greater extent in urban environments. All these factors may also contribute to explain our results. In addition, the time of establishment of the UGA may contribute explaining connectivity and biogeographical settings relationships. It is important to know that the existing pattern of green areas in Urban Madrid is relatively recent, most of these UGAs being less than 50 years old (Bautista Carrascosa et al. 2021). This timeframe might be insufficient to significantly influence colonization rates by increasing dispersal associated with the creation of these UGAs (Johnson et al. 2018). Finally, we think more research is needed about how ‘unnatural’ dispersal processes or human mediated dispersal is affecting urban connectivity values. There is a known relationship between connectivity and species richness through increased dispersal in natural systems (Herrera et al. 2017; Kindlmann and Burel 2008; Lookingbill et al. 2010), but there are new factors affecting dispersal processes in urban areas. Two main human activities underlie the alteration of natural dispersal, namely, the construction of buildings and the use of motor vehicles. These activities bring with them the movement of soil with seed banks, leading to what can be considered human mediated dispersal, disassociated from natural dispersal and connectivity (Hodkinson and Thompson 1997; Johnson et al. 2018; Wichmann et al. 2009). The deliberate introduction of ornamental species in urban areas can also contribute to the artificial homogenization, due to the presence of man-made soils rich in nutrients promoting unexpected colonization events (Kowarik 2005; Pyšek et al. 2010; Williams et al. 2009). Finally, non-natural animal dispersal facilitated by household pets, primarily dogs and cats, can also result in artificial homogenization (Nogales et al. 1996; Spennemann 2020). 4.3. Future research It is important to highlight the fact that the distribution of species richness in urban environments is significantly influenced by habitat microheterogeneity (Kowarik 2011; Lepczyk et al. 2017). Within the UGA system, and particularly within each individual UGA, a marked compartmentalization is observed (Jones and Leather 2012; Shanahan et al. 2011; Stenhouse 2004; Williams et al. 2009). Each UGA presents a diversity of habitats (Lepczyk et al. 2017; Lososová et al. 2012; Roy et al. 1999), environmental characteristics (Grimm et al. 2008; Li et al. 2023; Williams et al. 2009) and various forms of urban management (Goddard et al. 2010; Smith et al. 2005), ranging from undeveloped areas to historical parks and novel ecosystems. This habitat variability within each UGA could reveal a relationship between homogenization and the internal connectivity of each UGA, which may not be captured in our analysis. The Madrid UGA system follows this model, with high diversity of UGAs, some which host relatively large, diverse habitats, such as Casa de Campo (large green area on the west of the map in Fig. 5 ), or others which had traditionally been used for agricultural purposes but have now been turned into UGA (mainly in the east part of the city). There are also several nineteenth-century gardens with permanent humid microhabitats harbouring plants which are non-existent or rarely found elsewhere in the city. The influence of UGAs on biogeographic homogenization is a complex issue, the study of which we believe demands innovative approaches. Approaches proposed for future research should aim at improving the accuracy of the connectivity values found in our analysis. Considering the urban matrix surrounding UGAs as a homogeneous and completely unsuitable habitat for plant species (e.g., Godefroid and Koedam 2007; Williams et al. 2006), may offer misleading estimates of urban connectivity. More precisely, considering that the urban matrix evenly affects to ecological flows between UGAs, i.e., connectivity depends only on the Euclidean distance, may be less reliable than accounting for the heterogeneous nature of the urban space using resistance surfaces that allow a better assessment of individuals and genes flows (McRae and Beier 2007). Furthermore, more reliable connectivity estimates may be derived using improved identification and characterization of urban habitat patches through mapping small semi-natural areas outside UGAs that may play a role as stepping stones (Saura et al. 2014), and accounting for potential connectivity limitations that might be imposed by habitat heterogeneity within UGAs (De la Fuente et al. 2018). 5 Conclusions Urban environments are not isolated systems outside the natural world. They participate in biogeographical patterns and processes. Biogeographical barriers in cities still play a natural role even in highly transformed spaces. We have shown that spatial homogenization is not predominant. Moreover, it is a differential process depending on the flora group considered; the rare and habitat specific species being more prone to maintaining natural isolation. In contrast, the more common, widespread species are not filtered by urban settings and may easily colonise different biogeographical areas. Urban connectivity related to node size and natural dispersal parameters seems not to be particularly relevant in promoting barrier leaking or species richness, while there are several human induced processes capable of altering urban connectivity values; we propose human mediated dispersal and microheterogeneity of urban green areas being the most relevant. This study underlines the importance of the most abundant and generalist species, regardless of their natural origin (native or non-native), in explaining current urban patterns. In addition, our results also reveal that biogeographical isolation, promoting speciation and increasing biodiversity elsewhere (Burns 2019; Flantua et al. 2020; Mittelbach et al. 2007; Olden et al. 2001) is still operative in cities, in this case a large, old mediterranean city. Hence, urban spaces are able to maintain natural processes such as those involved in biogeographical isolation, and furthermore, they are able to host very rare flora associated with specific environments and even species which are endangered at national level (Kowarik 2011; Schwartz et al. 2013; Sweet et al. 2022; Zipperer 2010). Madrid is no different from the rest (Dominguez Lozano et al. 2023) and therefore we believe that future measures aimed at urban biodiversity conservation can be just as successful and indeed necessary as those applied in more natural settings. Declarations Funding Declaration: This work was supported by an INVESTIGO MITES grant financed through Next Generation EU funds [ grant number CT19/23-INV13 ]; and Ramón y Cajal grant from the Spanish Ministry of Science [grant number RYC2021-031797-I ]. Author Contribution RZ and FDL performed the conceptualization and the data curation.RZ and MB carried out the formal analyses and funding acquisition.RZ conducted the investigation.RZ, AG, MB and FDL refined the methodology.FDL managed and supervised the project. RZ, AG and MB were in charge of the software.RZ and FDL writing the original draft. Acknowledgement RZ was funded by an INVESTIGO MITES grant financed through Next Generation EU funds (CT19/23-INV13). MB was funded by a Ramón y Cajal grant from the Spanish Ministry of Science (RYC2021-031797-I). Plant data for the analysis were kindly provided by BOTMAD, a Madrid botany community dedicated to exploring and protect Madrid Urban flora. 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Ecology 87(12):3000–3006. https://doi.org/10.1890/0012-9658(2006)87[3000:LEOGPT]2.0.CO;2 Williams NSG, Schwartz MW, Vesk PA, McCarthy MA, Hahs AK, Clemants SE, Corlett RT, Duncan RP, Norton BA, Thompson K, McDonnell MJ (2009) A conceptual framework for predicting the effects of urban environments on floras. J Ecol 97(1):4–9. https://doi.org/10.1111/j.1365-2745.2008.01460.x Wittig R (2004) The origin and development of the urban flora of Central Europe. Urban Ecosyst 7:323–339. Zipperer WC (2010) Factors influencing non-native tree species distribution in urban landscapes. In: Muller N, Werner P, Kelcey JG (eds) Urban Biodiversity and Design. Wiley-Blackwell, pp 223–241. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7188073","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":496170373,"identity":"d12a2d07-f0fd-4b4c-a03d-5cac64b39fd6","order_by":0,"name":"Roberto Zeferino","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsUlEQVRIiWNgGAWjYFACHhAhx8BPqhZjBskGkrUYHCBWg3l778GHPyoM5IxvJD/dwFBRR1iLzJlzyQYSZwyMzW6kmd1gOHOYsBYJiRwzCcO2P4nbbuSw3WBsI8J5QC3mPxL/GdRvngHS8o8Ih4FsYTjYYJBgIAHS0sBMhBaec8mSDccMDGeceWZ2I+EYMX5h7z348UeNgTx/e/KzGx9qiHAYKkggVcMoGAWjYBSMAuwAAOfwN7+xPkejAAAAAElFTkSuQmCC","orcid":"","institution":"Complutense University of Madrid","correspondingAuthor":true,"prefix":"","firstName":"Roberto","middleName":"","lastName":"Zeferino","suffix":""},{"id":496170374,"identity":"228e49d9-4592-4db5-94bd-854c2230ff9c","order_by":1,"name":"Aitor Gastón","email":"","orcid":"","institution":"Technical University of Madrid","correspondingAuthor":false,"prefix":"","firstName":"Aitor","middleName":"","lastName":"Gastón","suffix":""},{"id":496170375,"identity":"2bb77091-985d-4f90-8d6e-cbc74e95e78b","order_by":2,"name":"Miguel Berdugo","email":"","orcid":"","institution":"Complutense University of Madrid","correspondingAuthor":false,"prefix":"","firstName":"Miguel","middleName":"","lastName":"Berdugo","suffix":""},{"id":496170376,"identity":"26d005e7-3243-4ad1-9c80-0b86b004317d","order_by":3,"name":"Felipe Domínguez Lozano","email":"","orcid":"","institution":"Complutense University of Madrid","correspondingAuthor":false,"prefix":"","firstName":"Felipe","middleName":"Domínguez","lastName":"Lozano","suffix":""}],"badges":[],"createdAt":"2025-07-22 14:23:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7188073/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7188073/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88531132,"identity":"a12babb2-5eb0-4d4a-98ea-0a601f5541df","added_by":"auto","created_at":"2025-08-07 11:34:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":260815,"visible":true,"origin":"","legend":"\u003cp\u003eLocation map of the study territory in the Autonomous Region of Madrid and in Iberia. Grey areas denote basic subtrates and ligh yellow acidic subtrates. Green areas are natural territories inside Madrid municipality excluded from our analysis.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7188073/v1/00464b81a943aa6ac08db130.png"},{"id":88532134,"identity":"288f917b-495c-458c-a598-cf48482415dc","added_by":"auto","created_at":"2025-08-07 11:50:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":242867,"visible":true,"origin":"","legend":"\u003cp\u003eNMDS values on its two main axes for the cells of Urban Madrid for the total urban flora. Blue dots show acidic cells, and red dots show basic cells. Ellipses show the 50% confidence interval, using the beta-dispersion method.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7188073/v1/abbcabf130ef83fded3cc6a7.png"},{"id":88531135,"identity":"04ce913e-9379-4be4-833a-5c249b540c1b","added_by":"auto","created_at":"2025-08-07 11:34:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":282921,"visible":true,"origin":"","legend":"\u003cp\u003eNMDS values ​​on the two main axes for cells of Urban Madrid considering the group of common flora (A) native flora (B) and non-native flora (C). Ellipses show the 50% confidence interval, using the beta-dispersion method.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7188073/v1/a4b8e3163924fc1629c1ff14.png"},{"id":88531138,"identity":"73b2b7ac-0343-4a56-b4e5-e8ad4d8eb919","added_by":"auto","created_at":"2025-08-07 11:34:20","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":194591,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of specialist flora in Urban Madrid. A: species richness of calcifuge flora. B: species richness of calcicole flora. The line between colours marks the separation between the acidic parent material (Yellow) and the basic parent material (Grey) in Urban Madrid following current biogeographical knowledge (Loidi, 2017). Note that the asymmetry could be even more pronounced since the presence of calcicole species in some acidic areas, such as some in the northwest part of the map, is mainly due to small outcrops of basic substrate within the acidic area, which are smaller than the scale used to map parent materials in Urban Madrid. The intensity of the colour indicates a higher presence of species, divided into 4 shades, from darker to lighter: a) 42 to 19; b) 18 to 10; c) 9 to 6; d) less than 6.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7188073/v1/174dcac24e4f43c0ef7dcf02.png"},{"id":88531143,"identity":"7556dcd6-33ea-4c46-8bbe-2c0d50e3be59","added_by":"auto","created_at":"2025-08-07 11:34:20","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":490115,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eMap of the distribution of dPCflux in the UGAs of the study area. The colours in the map represent quartiles. Green, top quartile; Yellow, third quartile; Orange, second quartile; Red, bottom quartile. Two large green zones located to the west and northeast of the study area are worthy of note (named Casa de Campo and Valdebebas respectively). The blue line denotes the course of the river Manzanares.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7188073/v1/4df88a73d323d7214ffeb4d6.png"},{"id":88531134,"identity":"56750c30-c7b4-4822-acc9-dbd7046c68ad","added_by":"auto","created_at":"2025-08-07 11:34:20","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":44323,"visible":true,"origin":"","legend":"\u003cp\u003eRobust regression between the different values of base-10 logarithm UTM connectivity and base-10 logarithm number of common species per UTM in Urban Madrid. Grey zone shows the 95% confidence interval for the regression line.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7188073/v1/16f36e3dab2a2094969d79b1.png"},{"id":88531928,"identity":"6b3fdae6-8b95-4b09-813e-fbc41bb662db","added_by":"auto","created_at":"2025-08-07 11:42:20","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":111331,"visible":true,"origin":"","legend":"\u003cp\u003eRobust regression between connectivity aligns the biogeographical border and specialist edaphic species outside their zone of specialization. A: calcicole flora on acidic parent material, B: calcifuge flora on basic parent materials. Grey zone shows the 95% confidence interval for the regression line.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7188073/v1/4bc134f42eec06a0d22bb385.png"},{"id":90061022,"identity":"29c0a3e0-ca5b-4ebd-8596-c63b6deb2adc","added_by":"auto","created_at":"2025-08-28 03:23:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2075712,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7188073/v1/22703ff4-ab82-450f-87ba-04647af8a440.pdf"},{"id":88532133,"identity":"5901f388-6837-4681-8f02-39c42390fd6f","added_by":"auto","created_at":"2025-08-07 11:50:20","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":4381627,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-7188073/v1/3479d90729098978251d3d46.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Testing barrier leaking and negative connectivity in biogeographical urban homogenization","fulltext":[{"header":"Highlights","content":"\u003cul\u003e\n \u003cli\u003eThe use of a comprehensive plant dataset that includes historical records from the 19th century and recent inventory data from the last three years.\u003c/li\u003e\n \u003cli\u003eCommon flora dilutes urban biogeographical barriers more effectively.\u003c/li\u003e\n \u003cli\u003eSpecialist flora causes asymmetrical biogeographical homogenization.\u003c/li\u003e\n \u003cli\u003eNo direct relationship was found between urban connectivity and homogenization.\u003c/li\u003e\n \u003cli\u003eCities, despite alterations, retain biogeographical patterns and processes.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eBiotic homogenization is a process which is highly associated with the Anthropocene (Daru et al. 2021). It has negative consequences (Olden et al. 2004) in ecological (Kinzig et al. 2013), economic (Hanley and Perrings 2019; Edwards and Abivardi 1998) and evolutionary (Moritz 2002) realms. Traditionally, homogenization has been closely associated with the role of non-native species in urban settings (McKinney and Lockwood 1999), as urban habitats are more receptive to non-native species (Pyšek et al. 2010; Roy et al. 1999), which in turn have been responsible for increasing overall species richness (Lososov\u0026aacute; et al. 2012; McKinney 2008; Wania et al. 2006). Thus, temporal aspect of homogenization is widely acknowledged, and extensive and rapid changes associated with many years of urban planning, including not only housing and ever-increasing daily traffic, but also horticulture and green design, have contributed to the present characteristic turnover of urban species (Hust\u0026eacute; and Boulinier 2007; Lososov\u0026aacute; et al. 2016), increasing the presence of nonnative species. However, non-native homogenization is just one particular type of a more participated process.\u003c/p\u003e\u003cp\u003eThus, homogenization can also embrace other fractions of the current urban biota assemblages, reflected not only in the pools of non-native species but also in non-natural assemblages of native species, since urban biodiversity is the result of intermingled species origins (Kowarik 2011; La Sorte et al. 2007; Lundholm and Marlin 2006; McKinney 2002; Padull\u0026eacute;s Cubino et al. 2019; Palma et al. 2016; Wittig 2004). Recent extinction and colonisation events have contributed to the appearance of new urban native species (Duncan et al. 2011; Hahs et al. 2009; Hust\u0026eacute; and Boulinier 2007), with some reaching high levels of urban abundance (Blair 1996), characterised by broader niche properties (Palacio 2019; Palacio 2020) and therefore contributing to urban homogenization as well (Blair 1996; Kark et al. 2007).\u003c/p\u003e\u003cp\u003eThis broader concept of homogenization is not yet considered, and little is known about how natural factors, such as regional or biogeographical scale patterns, may be affected by non-natural movements of the biota in cities (Li et al. 2023; Marchetti et al. 2006). For example, we can expect that the anthropogenic leaking of biogeographical barriers in a city will also contribute to homogenization as species from different biogeographical origins may come to live together. Moreover, this biogeographical homogenization may have different effects according to the origin of the biota, that is, whether they are rare or narrowly distributed, common or widespread, as well as whether they are specialist or generalist or native or non-native.\u003c/p\u003e\u003cp\u003eUrban connectivity may play a role in this type of biogeographic homogenization of biota. Connectivity is a spatial trait that depends on distribution and shape of habitat patches (in the case of cities, urban green areas) as well as on species dispersal abilities (Saura and Pascual-Hortal 2007; Taylor et al. 1993). The positive function of connectivity is widely accepted in biodiversity management. Better connectivity promotes dispersion, increases gene flow, and precludes demographic decline (Baguette et al. 2013; Hansson 1991; Lookingbill et al. 2010) while negative effects have rarely been detected (Orrock and Damschen 2005). Thus, regarding homogenization, negative connectivity can be seen as an actor fostering unnatural assemblages of native urban flora due to the breaking down of natural isolation that may occur as urban connectivity increases. This could be of particular concern when we focus on the urban public recreation park network, given the ability of these spaces to support biodiversity (Talal and Santelmann 2019). The biodiversity of public parks is driven by natural factors (mainly climate and regional context) as well as by anthropogenic alterations and in fact species composition in green urban spaces is closely related to management actions (Ibsen et al. 2020; Threlfall et al. 2017). Moreover, studies have shown that in some cases they do not follow natural patterns of species diversity (Al\u0026oacute;s Ort\u0026iacute; et al. 2022). Hence, it is crucial to explore the way in which negative connectivity among urban green spaces may contribute to the crossing of biogeographical barriers in urban settings, resulting in greater urban homogenization. This increased understanding of the current situation could help to improve our ability to manage urban biodiversity with the aim of protecting natural assemblages also in urban scenarios.\u003c/p\u003e\u003cp\u003eMadrid is a large European city located in a mediterranean environment. Interestingly, it is situated between two distinct biogeographical regions (Grijalbo Cervantes 2019; Izco 1984; Rivas-Martinez et al. 1987) associated with the parent material of the soils. The city lies on an area of confluence between siliceous sedimentary rocks (mainly arkoses) and carbonate or sulphate rich sedimentary materials (mainly marls and gypsum). The soil types partially explain urban plant diversity (Jogan et al. 2022; K\u0026uuml;hn et al. 2004), so in the Madrid case there is a unique opportunity to study the effect of edaphic barriers, since this city is home to two distinct types of edaphic flora.\u003c/p\u003e\u003cp\u003eIn addition to the abovementioned geological aspect of Madrid, the city has an extensive system of managed green spaces within urban areas, with older public gardens in the downtown area as well as modern green spaces in the suburban areas. Finally, there is a relatively complete knowledge of the distribution of wild plant species within the city limits, thanks to readily available historical work along with a very recent inventory of Madrid flora (Bot Mad et al. 2023; Cutanda 1861; Garc\u0026iacute;a 1983). Given this interesting context, Madrid provides a suitable scenario for testing several hypotheses related to the link between spatial homogenization types, origin of urban biotas, biogeographical barriers, and connectivity.\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003e1.1. Objectives\u003c/h2\u003e\u003cp\u003eOur main objective is to test whether biogeographical homogenization has been taking place in an urban environment, and if so, to what extent. Cities may be compatible with the natural process of biogeographical isolation, in which the effect of biogeographical barriers is apparent, or on the contrary, urban processes may in fact dilute the biogeographical barrier. To test these notions, we measure urban biogeographical homogenization across different flora elements. Thus, we analyse the way in which spatial urban homogenization affect: 1) total urban flora, 2) native and non-native groups, 3) common (in opposition to rare) plants and 4) generalist and specialist plants (flora of different lithologic origins).\u003c/p\u003e\u003cp\u003eSecondly, we explore urban connectivity in relation to urban homogenization. The extent and location of public parks may encourage an unnatural increase in species movements and colonization thus creating greater opportunities for spatial homogenization. To explore the role of negative connectivity in fostering the dilution of biogeographical barriers with regard to flora in the city of Madrid, we test the hypothesis that areas with increasing connectivity are those where greater spatial homogenization is occurring (in terms of plant overall richness). If this is so, we can expect plant responses to the present connectivity and biogeographical barriers to differ according to both lithological preferences of the species and distribution range (common plants). We study the hypothesis at two levels: first using the whole territory of the Madrid city and secondly selecting only those areas configuring the biogeographical border inside the city.\u003c/p\u003e\u003c/div\u003e"},{"header":"2 Material and Methods","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Study Area\u003c/h2\u003e\u003cp\u003eThe study area, hereafter referred to as Urban Madrid, coincides with the area considered in the most recently published checklist (Bot Mad et al. 2023). This region covers approximately 36,041 hectares and consists of exclusively urban areas within the city. 3.22\u0026nbsp;million people live within this area (INE, 2024); 8,934 inhabitants/km\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe suburban and natural areas inside the city limits were excluded from the study since these areas lacked distinctive urban characteristics. Hence, areas with less than 1000 inhabitants/km\u003csup\u003e2\u003c/sup\u003e were not taken into consideration, nor were areas in which less than 50% of the area was concrete/asphalt-covered, or parts of the city bordering rural areas (suburban areas) (MacGregor-Fors 2011). Furthermore, we excluded zones on the outskirts of the city with minimal anthropogenic disturbance that retain their natural connectivity with river basins and drainage networks and where significant earthworks have not taken place, such as Monte del Pardo or Pinar de Valdelatas (natural areas) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe most updated Mediterranean biogeographical regionalization for Iberia established six provinces and Madrid city lies between two of them, central and west Mediterranean provinces (Rivas-Martinez, et al. 2017). This border has been acknowledged since early times and is established based on strong lithology differences among floras of both sides (Izco 1984). Biogeographical borders are difficult to set at local scales, and we decided to establish the border line between both provinces for Urban Madrid following current knowledge of the lithology and parent soil origin (extracted from IGME, (Goy Goy et al. 2023). As a result, two city areas for each biogeographical provinces were established, one having soils of a calcifuge nature (henceforth \u0026lsquo;acidic\u0026rsquo;), covering 24,601 ha and the other, covering 11,440 ha., presenting soils of an alkaline (henceforth \u0026lsquo;basic\u0026rsquo;) nature.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Data\u003c/h2\u003e\u003cp\u003ePlant species presence and abundance data were taken from the Flora and Conservation Database for Urban Madrid (FCDUM, here on, Bot Mad et al. 2023). This database contains over 30,000 records for the city of Madrid, of which 18,700 are within our study area. A total of 1,516 species were considered for Urban Madrid. Spatial data were in two different formats, 1x1 km utms quads and more precise geographical coordinates (GPS precision). FCDUM only considers vascular flora, and both native and non native plants, the latter excluding cultivated and horticultural plants. Native and non native status was based on the criteria of Bot Mad et al. 2023.\u003c/p\u003e\u003cp\u003eThe urban green areas (UGAs) encompass public parks, forest parks, river spaces, green streets and infrastructures, semi-natural vegetation, and undeveloped plots (UTE Tecnigral-Dasotec 2016). Green buildings, street trees, private gardens, and cemeteries were excluded from this study as they represent less than 0.1% of the total UGAs in Madrid. In accordance with these criteria, a total of 11,494 UGAs were identified, ranging in size from 1 m\u003csup\u003e2\u003c/sup\u003e to over 2.4 km\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAll cartographic data, species richness and abundance, distribution of UGAs and lithology (extracted from IGME, (Goy Goy et al. 2023) were referenced to a 1x1 km UTM grid for Urban Madrid (159 UTM cells in total). The number of records per species in each cell was used to create a presence/absence of flora matrix per cell.\u003c/p\u003e\u003cp\u003eThe lithology based on chemical composition was recorded in a binary manner (acidic, for siliceous materials, and basic for carbonate and sulphate materials) for each cell. To perform this transformation, the lithological information was simplified by grouping all types of gypsum and gypsum clays into the 'basic' category and all sandy clays and riverbeds into the 'acidic' category, excluding cells with mixed parent material from the analysis (23 in total).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Analyses\u003c/h2\u003e\u003cp\u003eThe presence/absence of flora matrix was transformed into a dissimilarity matrix using the Jaccard index, chosen for its effectiveness with binary data (Choi et al. 2010; Chung et al. 2019). This dissimilarity matrix was analysed using a PERMANOVA (Anderson 2017) in order to identify significantly different groups of plants according to the biogeographical areas defined (acidic and basic cells). The analysis was performed using ADONIS (Anderson 2001) to obtain the most significant values. We used a reduced model, as the matrix is not square, and 9,999 permutations were performed (Bakker 2024).\u003c/p\u003e\u003cp\u003eIn addition, we used dissimilarity matrix values to perform an ordinal analysis based on the Multidimensional Scaling Analysis (NMDS) technique (Kruskal and Hill 1964; Shepard 1962; Shepard and Arabie 1979). We decided to use this type of analysis as it is a commonly used statistical tool in community ecology (Schaefer et al. 2005), conservation (Ruh\u0026iacute; et al. 2017), biogeography (Kreft and Jetz 2010) and land management (Dwyer et al. 2019). To obtain groups with a 50% confidence interval, we used the beta-dispersion method (Anderson 2017).\u003c/p\u003e\u003cp\u003eWe carried out this analysis for three different data sets from FCDUM. Firstly, we took into consideration the total urban vascular flora (1501 species). Secondly, we selected only the common plants, defined as those plants with a number of observations exceeding the 90th percentile (more than 40 records per species) comprising 159 species. Finally, we used the differentiation among native (1279 species) and non-native plants (143 species) for the third analysis.\u003c/p\u003e\u003cp\u003eTo evaluate whether the edaphic preferences of the plants affect the relationship of the flora with connectivity and biogeographical barriers, the species associated with each parent material (acidic/basic) were identified. To classify the species, a chi-square statistic was used. Species with less than 5 occurrences in the area were not considered in this analysis to ensure the significance of the results and avoid either empty cells or cells with a frequency of less than 5% in the chi-square analysis (Tallarida and Murray 1987). After applying this filter, the database extracted from FCDUM was reduced from 1516 to 501 species. We use the term 'generalists', for plants showing no preference for any parent material, 'calcifuge flora', for plants associated with acidic parent material, and 'calcicole flora', for plants growing on basic substrates.\u003c/p\u003e\u003cp\u003eTo address our second hypothesis, that urban connectivity affects spatial urban homogenization, we first assessed the role of each UTM cell in the connectivity for plant species. Hence, we selected all the UGAs in Urban Madrid with an area greater than 2,500 m\u0026sup2;. This size was deemed biologically significant enough to host natural colonization and extinction processes. After applying this filter, we analysed 1,856 out of the total 11,494 UGAs. The Probability of Connectivity (PC) index was calculated as a measure of the overall connectivity of the system (Saura and Pascual-Hortal 2007), i.e., the probability that two randomly selected UGAs are actually connected. The area of each UGA was used as an estimator of the habitat availability and the probability between pairs of UGAs was estimated using Euclidean distances. The contribution of each UGA to overall connectivity was calculated by measuring the relative decrease in PC resulting from the removal of each UGA. We considered a maximum dispersion value of 1050 m, as this may be considered the usual maximum dispersal distance for most flora (Corlett 2009). We considered the flux component of the probability of connectivity (Saura and Rubio 2010) that measures the contribution to connectivity of each UGA when that UGA is the starting or ending patch of each connection between patches.\u003c/p\u003e\u003cp\u003eWe analysed the relationship between connectivity and biogeographical homogenization using robust regression. This method allows the effect of outliers to be reduced in the regression of the data (Huang et al. 2016). As the dependent variable, we used the decimal logarithm of species records per grid, and as the independent variable, the decimal logarithm of connectivity per cell.\u003c/p\u003e\u003cp\u003eFor this last analysis we used two approaches, first we studied connectivity-homogenization relationship across the whole study area, Urban Madrid, using the number of common species present. As connectivity values, we calculated the dPCflux index (Saura and Rubio 2010). As a measure of homogenization, we consider the number of common plants per square, assuming that high common species richness denotes higher homogenization.\u003c/p\u003e\u003cp\u003eSince the relationship between connectivity and biogeographical homogenization may be mediated by distance to the border and habitat specificity, we also performed a second approach. We assumed that the effect of connectivity onto biogeographical homogenization is gradual, if strong the signal maybe detected in both data set, if weak only around the border and for the most sensitive plants, therefore this second approach. We analysed only the area around the biogeographical border. As a measure of homogenization we took into consideration the number of specialist species from one type of parent material present in cells of the other parent material. Thus, in this case, for homogenization to take place, we would expect a positive correlation among calcicole plants and acidic cells and vice versa, a positive correlation between calcifuge plants and basic cells along the border. We selected cells within the maximum dispersal distance established in our analysis (1050 m) on both sides of the border line, 79 UTM cells in total. In this latter case, we only considered connections between pairs UGAs from different regions. To do so, we used an adaptation of the dPCflux index consisting of considering only the area of the source habitat patches and multiplying it by the probability of connection between the two nodes (without considering the area of the destination patch).\u003c/p\u003e\u003cp\u003eOn considering those two data sets we take into account both the effect of barrier leaking and the overall plant richness distribution in the city. In both cases, dPCflux values were upscaled from UGAs to 1 km cells using area weighted sums.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results","content":"\u003cp\u003e\u003cspan\u003e\u003c/span\u003e\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003e3.1 Total urban flora\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eFigure\u0026nbsp;2. NMDS values on its two main axes for the cells of Urban Madrid for the total urban flora. Blue dots show acidic cells, and red dots show basic cells. Ellipses show the 50% confidence interval, using the beta-dispersion method.\u003c/p\u003e\n\u003cp\u003eTaking into consideration the whole urban flora set in the city of Madrid, the PERMANOVA analysis identifies significantly different plant compositions for the two biogeographical areas, basic and acidic (R-square\u0026thinsp;=\u0026thinsp;0.027, Pseudo-F\u0026thinsp;=\u0026thinsp;2.959 and p-value\u0026thinsp;=\u0026thinsp;0.0001). In addition, the NMDS results also differentiate both areas, as shown by the two ellipses produced by the beta-dispersion (Fig.\u0026nbsp;2). However, this differentiation is not strong, as these two cell groups overlap substantially in Fig.\u0026nbsp;2., and variance in the NMDS analysis is not high (Stress\u0026thinsp;=\u0026thinsp;0.221). 39% of species appear on both parent materials.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2. Different groups of urban flora\u003c/h2\u003e\n \u003cp\u003eExploring flora subgroups, PERMANOVA results show that differences among regions are statistically significant in all cases (a. common plants: R-square\u0026thinsp;=\u0026thinsp;0.032, pseudo-F\u0026thinsp;=\u0026thinsp;3.067 and p-value\u0026thinsp;=\u0026thinsp;0.0001; b. native plants: R-square\u0026thinsp;=\u0026thinsp;0.295, pseudo-F\u0026thinsp;=\u0026thinsp;3.128 and p-value\u0026thinsp;=\u0026thinsp;0.0001 and c. non-native plants: R-square\u0026thinsp;=\u0026thinsp;0.024, pseudo-F\u0026thinsp;=\u0026thinsp;2.125 and p-value\u0026thinsp;=\u0026thinsp;0.001). However, Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e again reveals that the UTM groups share a large amount of their respective flora compositions as shown by the overlap of the ellipses and variance values (common plants: Stress\u0026thinsp;=\u0026thinsp;0.210; native plants: Stress\u0026thinsp;=\u0026thinsp;0.210; non-native plants\u0026thinsp;=\u0026thinsp;0.221). The group of common plants seems to be the most affected by homogenization as centroids of the ellipses of the two cell groups are close together (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA).\u003c/p\u003e\n \u003cp\u003eThese results suggest that the two biogeographic areas are consistent, they shelter different compositions of flora, considering the urban flora as a whole as well as specific groups, common species, or native and non-native species. However, the NMDS results do not point to strong differences, and we cannot dismiss some homogenization in the urban flora of Madrid. This is specially true when centroids are closer (common and non-native flora are considered).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3. Soil parent material preference flora\u003c/h2\u003e\n \u003cp\u003eAccording to parent material plant preferences within the study area, 29 calcifuge species and 48 calcicole species were identified (see Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, supplementary material). Figure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e shows the urban distribution for both, revealing an asymmetric distribution of specialist flora. This asymmetry is quantitatively evident, as the presence of calcifuge flora is up to 7.72 times greater in the basic area than calcicole flora in the acidic area (see supplementary material).\u003c/p\u003e\n \u003cp\u003eTherefore, considering this differential proportion of edaphic specialist species, the biogeographical barrier has an asymmetrical effect, affecting calcicole flora to a greater extent since calcicole species appear less capable of crossing into acidic areas. In spite of the fact that basic parent material is usually more demanding and stressful for plants, some calcifuge plants are also present in this territory in Urban Madrid.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4. Connectivity and homogenization\u003c/h2\u003e\n \u003cp\u003eWe produced the map of Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e to show how connectivity is distributed across Madrid UGAs.\u003c/p\u003e\n \u003cp\u003eThe map highlights the significance of size and topology in the flux fraction of connectivity. Larger areas tend to exhibit higher dPCflux values. Spatial arrangement also plays a crucial role in determining dPCflux; relatively small UGAs have higher dPCflux values if they are close (see the polygons surrounding the course of the river). If negative connectivity is taking place, we may expect that UGAs with higher dPCflux values in this map (important nodes of connectivity) would be also sites with higher values of common species richness, the group identified as more prone to homogenization. However, according to Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, there is no significant relationship between connectivity in UGAs and the richness of common flora in Urban Madrid (p-value of 0.454 after 1000 bootstrap repetitions, applied to the slope coefficient of a robust regression between connectivity and species richness). Thus, in the current UGA system, cells with higher connectivity do not harbour a greater number of common species, therefore they are not homogenization sites.\u003c/p\u003e\n \u003cp\u003eTo confirm that the lack of relationship between connectivity and homogenization was consistent across areas and species, we analysed connectivity through the specialist edaphic flora along the biogeographical border line. Thus, we performed two new robust regressions for each type of edaphic specialist present on the other side of the border (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e), one case focusing on calcifuge plants growing in basic cells, and the other on calcicole plants in acidic cells, in both cases considering only the biogeographic border (79 cells in total, 49 for acidic cells and 30 for basic cells). Figure \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e shows no relationship in either case (calcifuge flora on basic parent material, p-value of 0.950; calcicole flora on acidic parent materials, p-value of 0.808).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eBiogeographical homogenization is not consistent in urban Madrid. Overall, flora segregation occurs across the biogeographical barrier. Distribution of UGAs and connectivity does not contribute to dilute the effect of the barrier either. However, our results indicate that the response of the flora to homogenization is far from simple, and that urban biogeographic homogenization may be a gradual and differential process, depending on the flora type involved.\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Role of flora groups in contributing to biogeographical homogenization\u003c/h2\u003e\u003cp\u003eThe lack of specialists has been denoted as a major cause for homogenization (Clavel et al. 2011). In fact, this process has been measured in some particular habitats (A specialist-generalist classification of the arable flora and its response to changes in agricultural practices), in our work the specialist group (acidic and calcicole plants) has shown biogeographical segregation, as certain species appear predominantly on acidic parent materials (acidic flora) and others occur on basic (calcicole flora) (as shown by the chi-square analysis). Moreover, the effect of soil ph on plant composition and richness have been widely studied (P\u0026auml;rtel 2002, Crespo-Mendes et al. 2019). There are many examples of soil ph explain plant diversity at local scales (Gough et al. 2000; Schuster and Diekmann 2003; Sebasti\u0026aacute; 2004) For Iberian flora, edaphic factors are fundamental to explain biogeography patterns, and it is a clear distinction between acidic and calcicole plant distribution (Buira et al. 2021).\u003c/p\u003e\u003cp\u003eOur results show the barrier segregate most for calcicole flora, and there is no biogeographical leaking in this case. These species are adapted to edaphically stressful parent materials and are less commonly found in urban environments (Escudero et al. 2015; Mota et al. 2011). Calcicole flora resulting from edaphic evolutionary selection form highly specialized communities that are much more demanding than calcifuge species. This hyper-specialization makes them poor competitors in highly dynamic urban environments (Evans et al. 2011; Hansson 1991; Mota et al. 2011). However, our results reveal a consistent asymmetric biogeographical homogenization when considering acidic plants. This flora contributes most towards weakening the biogeographical barrier separating the two edaphic areas, given that these species are also found in areas with basic parent material (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e). 413 occurrences of acidic species on basic substrates were recorded compared to 193 occurrences of calcicole plants on acidic substrates (weighted according to the size of each area, the cross-border occurrence of acidic species is 7.72 times that of calcicole species). Acidic flora, despite being specialist species, are not as demanding as calcicole flora, and many of the records correspond to disturbed areas such as road verges and urban wastelands in both biogeographical territories in Urban Madrid.\u003c/p\u003e\u003cp\u003eConsidering non-native and native flora groups, it is known that they to exhibit different behavioural traits in urban settings (Lososov\u0026aacute; et al. 2012; Pyšek et al. 2010), just as more abundant flora tend to employ different strategies to rarer flora (Levins 1968; MacGregor-Fors and Schondube 2011; Marvier et al. 2004). Our results show that, in the case of the city of Madrid, there is no distinction between the two different floras based on the two edaphic biogeographical provinces. We observe that both native and non-native flora contribute similarly to biogeographic characterization, with no significant differences in their response to the biogeographic barrier. It seems that in highly dynamic, modified urban environments, the origin of the flora is secondary, while tolerance to changes plays a fundamental role, both in native and non-native species.\u003c/p\u003e\u003cp\u003eIn accordance with other authors, that have found different rates of homogenization depending on composition and biogeography (Pearse et al. 2018), we also detect differential homogenization according to plant groups or composition, thus common urban species are the most sensible to biogeographical homogenization in our case (centroids in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). These are mainly ruderal species, with known ability for colonization and resistance to frequent disturbance, while also being widely distributed beyond the studied area (positive correlation between number of UTM cells in urban Madrid and number of UTM cells in whole Iberia for this flora set, data not shown). The characteristics of the urban environment (extreme fragmentation and unpredictable colonization sites) further favour this species group (Evans et al. 2011; MacGregor-Fors and Schondube 2011; Pellissier et al. 2012; Shochat et al. 2006; Williams et al. 2009), which dominate the flora of Urban Madrid. It has been highlighted that common species also tend to be generalist species (Denelle et al. 2020), and in our case this seems to be true, as both biogeographical provinces in Urban Madrid (as delimited by the two groups of edaphic UTMs) share up to 39% of the total species. In addition, we show that of the 501 total species considered in the chi-square analysis, 85% were present in both biogeographical areas of Urban Madrid and therefore are termed generalist species. Some authors have reported similar figures for homogenization (Lososov\u0026aacute; et al. 2012; Price et al. 2020; Rahel 2000).\u003c/p\u003e\u003cp\u003eFrom an overall perspective the different groups of flora differ in their responses to the biogeographical barrier, making homogenization a gradual and differential process. However, rather than depending on their origin (native or non-native), this difference is more related to their abundance and edaphic preferences. It is the common and generalist flora that contribute most towards diluting the barrier. The biogeographical homogenization caused by specialist flora (acidic/calcicole) is asymmetrical, the ratio of connectivity to calcicole in terms of contribution to the homogenization process being 7.72:1. As for the entire flora, the two areas share a noticeable proportion of the same flora (39%).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Connectivity and Human-Mediated Dispersal\u003c/h2\u003e\u003cp\u003eThe creation of new UGAs has been linked to an increase in artificial connectivity (Czarnecka et al. 2013; Goddard et al. 2010; Lepczyk et al. 2017). Equally, some authors have also suggested that new UGAs contribute to homogenization (Rahel 2007; Strecker and Brittain 2017; Trentanovi et al. 2013). Our results do not support the assumption that increased urban connectivity necessarily leads to greater urban homogenization. This lack of relationship is evident at two levels of analysis. On the one hand, considering the number of common ruderal generalist plants across Urban Madrid as a whole, we found no relationship to an increase in UGA connectivity per cell (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The increase in overall plant richness in cities is closely related to homogenization of this species pool (McKinney 2008; Knapp 2010), but not to connectivity in Urban Madrid. On the other hand, considering only the cells around the border, the increase in asymmetric biogeographical homogenization recorded showed no relationship with the better-connected cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe most direct explanation for this situation is that the positive effect on the dispersal and colonization processes of a better-connected network does not counteract the natural effect of the biogeographical barrier. Our results suggest that the barrier is still in place. This barrier robustness identifies gypsum and gypsum clays areas and calcicole floras as potential biodiversity reservoirs, and less prone to homogenization and invasion phenomena.\u003c/p\u003e\u003cp\u003eEqually important, in urban areas, connectivity tends to be influenced by 'artificial dispersal barriers', not found in natural environments. For example, building height, extension of paved areas (Riley et al. 2014; Robertson et al. 2013), areas with artificial lighting and noise (Hale et al. 2015; Ware et al. 2015), and competition with invasive species (Kennedy et al. 2002; Lockwood and Welbourne 2023; Trentanovi et al. 2013), occur either exclusively or at least to a greater extent in urban environments. All these factors may also contribute to explain our results.\u003c/p\u003e\u003cp\u003eIn addition, the time of establishment of the UGA may contribute explaining connectivity and biogeographical settings relationships. It is important to know that the existing pattern of green areas in Urban Madrid is relatively recent, most of these UGAs being less than 50 years old (Bautista Carrascosa et al. 2021). This timeframe might be insufficient to significantly influence colonization rates by increasing dispersal associated with the creation of these UGAs (Johnson et al. 2018).\u003c/p\u003e\u003cp\u003eFinally, we think more research is needed about how \u0026lsquo;unnatural\u0026rsquo; dispersal processes or human mediated dispersal is affecting urban connectivity values. There is a known relationship between connectivity and species richness through increased dispersal in natural systems (Herrera et al. 2017; Kindlmann and Burel 2008; Lookingbill et al. 2010), but there are new factors affecting dispersal processes in urban areas. Two main human activities underlie the alteration of natural dispersal, namely, the construction of buildings and the use of motor vehicles. These activities bring with them the movement of soil with seed banks, leading to what can be considered human mediated dispersal, disassociated from natural dispersal and connectivity (Hodkinson and Thompson 1997; Johnson et al. 2018; Wichmann et al. 2009). The deliberate introduction of ornamental species in urban areas can also contribute to the artificial homogenization, due to the presence of man-made soils rich in nutrients promoting unexpected colonization events (Kowarik 2005; Pyšek et al. 2010; Williams et al. 2009). Finally, non-natural animal dispersal facilitated by household pets, primarily dogs and cats, can also result in artificial homogenization (Nogales et al. 1996; Spennemann 2020).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Future research\u003c/h2\u003e\u003cp\u003eIt is important to highlight the fact that the distribution of species richness in urban environments is significantly influenced by habitat microheterogeneity (Kowarik 2011; Lepczyk et al. 2017). Within the UGA system, and particularly within each individual UGA, a marked compartmentalization is observed (Jones and Leather 2012; Shanahan et al. 2011; Stenhouse 2004; Williams et al. 2009). Each UGA presents a diversity of habitats (Lepczyk et al. 2017; Lososov\u0026aacute; et al. 2012; Roy et al. 1999), environmental characteristics (Grimm et al. 2008; Li et al. 2023; Williams et al. 2009) and various forms of urban management (Goddard et al. 2010; Smith et al. 2005), ranging from undeveloped areas to historical parks and novel ecosystems. This habitat variability within each UGA could reveal a relationship between homogenization and the internal connectivity of each UGA, which may not be captured in our analysis. The Madrid UGA system follows this model, with high diversity of UGAs, some which host relatively large, diverse habitats, such as Casa de Campo (large green area on the west of the map in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e), or others which had traditionally been used for agricultural purposes but have now been turned into UGA (mainly in the east part of the city). There are also several nineteenth-century gardens with permanent humid microhabitats harbouring plants which are non-existent or rarely found elsewhere in the city.\u003c/p\u003e\u003cp\u003eThe influence of UGAs on biogeographic homogenization is a complex issue, the study of which we believe demands innovative approaches. Approaches proposed for future research should aim at improving the accuracy of the connectivity values found in our analysis. Considering the urban matrix surrounding UGAs as a homogeneous and completely unsuitable habitat for plant species (e.g., Godefroid and Koedam 2007; Williams et al. 2006), may offer misleading estimates of urban connectivity. More precisely, considering that the urban matrix evenly affects to ecological flows between UGAs, i.e., connectivity depends only on the Euclidean distance, may be less reliable than accounting for the heterogeneous nature of the urban space using resistance surfaces that allow a better assessment of individuals and genes flows (McRae and Beier 2007). Furthermore, more reliable connectivity estimates may be derived using improved identification and characterization of urban habitat patches through mapping small semi-natural areas outside UGAs that may play a role as stepping stones (Saura et al. 2014), and accounting for potential connectivity limitations that might be imposed by habitat heterogeneity within UGAs (De la Fuente et al. 2018).\u003c/p\u003e\u003c/div\u003e"},{"header":"5 Conclusions","content":"\u003cp\u003eUrban environments are not isolated systems outside the natural world. They participate in biogeographical patterns and processes. Biogeographical barriers in cities still play a natural role even in highly transformed spaces. We have shown that spatial homogenization is not predominant. Moreover, it is a differential process depending on the flora group considered; the rare and habitat specific species being more prone to maintaining natural isolation. In contrast, the more common, widespread species are not filtered by urban settings and may easily colonise different biogeographical areas. Urban connectivity related to node size and natural dispersal parameters seems not to be particularly relevant in promoting barrier leaking or species richness, while there are several human induced processes capable of altering urban connectivity values; we propose human mediated dispersal and microheterogeneity of urban green areas being the most relevant.\u003c/p\u003e\u003cp\u003eThis study underlines the importance of the most abundant and generalist species, regardless of their natural origin (native or non-native), in explaining current urban patterns. In addition, our results also reveal that biogeographical isolation, promoting speciation and increasing biodiversity elsewhere (Burns 2019; Flantua et al. 2020; Mittelbach et al. 2007; Olden et al. 2001) is still operative in cities, in this case a large, old mediterranean city. Hence, urban spaces are able to maintain natural processes such as those involved in biogeographical isolation, and furthermore, they are able to host very rare flora associated with specific environments and even species which are endangered at national level (Kowarik 2011; Schwartz et al. 2013; Sweet et al. 2022; Zipperer 2010). Madrid is no different from the rest (Dominguez Lozano et al. 2023) and therefore we believe that future measures aimed at urban biodiversity conservation can be just as successful and indeed necessary as those applied in more natural settings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding \u003cem\u003eDeclaration:\u0026nbsp;\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003e\u003cem\u003eThis work was supported by\u003c/em\u003e an INVESTIGO MITES grant financed through Next Generation EU funds [\u003cem\u003egrant number\u003c/em\u003e CT19/23-INV13\u003cem\u003e]; and\u003c/em\u003e Ram\u0026oacute;n y Cajal grant from the Spanish Ministry of Science \u003cem\u003e[grant number\u003c/em\u003e RYC2021-031797-I\u003cem\u003e].\u003c/em\u003e\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eRZ and FDL performed the conceptualization and the data curation.RZ and MB carried out the formal analyses and funding acquisition.RZ conducted the investigation.RZ, AG, MB and FDL refined the methodology.FDL managed and supervised the project. RZ, AG and MB were in charge of the software.RZ and FDL writing the original draft.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eRZ was funded by an INVESTIGO MITES grant financed through Next Generation EU funds (CT19/23-INV13). MB was funded by a Ram\u0026oacute;n y Cajal grant from the Spanish Ministry of Science (RYC2021-031797-I). Plant data for the analysis were kindly provided by BOTMAD, a Madrid botany community dedicated to exploring and protect Madrid Urban flora. Urban green areas maps were provided by the Dt. of water management and green areas of Madrid city council. 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Wiley-Blackwell, pp 223\u0026ndash;241.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Urban biodiversity, Urban conservation, Urban flora, Urban Biogeography, Madrid, Public parks","lastPublishedDoi":"10.21203/rs.3.rs-7188073/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7188073/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHomogenization is a process which is particularly relevant in urban environments. We focus on the flora of a large mediterranean Spanish city, Madrid, located along two different edaphic biogeographical regions. We test whether biogeographical homogenization, in terms of anthropogenic biogeographical barrier crossing, has been taking place, and to what extent.\u003c/p\u003e\u003cp\u003eSecondly, we attempt to shed light on the relationship between urban connectivity and urban homogenization. We use the public parks system in Madrid to test whether these spaces could foster an unnatural increase in species movements, and therefore a \u0026lsquo;leakage\u0026rsquo; in the biogeographical barrier, diluting the barriers among territories and providing increased opportunities for homogenization.\u003c/p\u003e\u003cp\u003eBiogeographical homogenization is not consistent in urban Madrid. Our results identify the common and generalist flora as the most significant plant set in terms of diluting the barrier. The biogeographical homogenization caused by specialist flora (calcifuge/calcicole) is asymmetrical, with a ratio of 7.72:1 of calcifuge to calcicole. Our results do not support the assumption that more urban connectivity is related to greater urban homogenization. The biogeographical barrier, together with human mediated dispersal and the microheterogeneity of urban green areas are possible factors that may explain this lack of relationship.\u003c/p\u003e\u003cp\u003eBiogeographical barriers in cities continue to play a natural role and homogenization is a differential process resulting in distinct effects depending on plant ecology and biogeography. Although urban spaces are highly altered, they host several groups of floras, and they contribute to biogeographical patterns and processes. Hence, there is still room for biological conservation in cities.\u003c/p\u003e","manuscriptTitle":"Testing barrier leaking and negative connectivity in biogeographical urban homogenization","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-07 11:34:16","doi":"10.21203/rs.3.rs-7188073/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"49213cb4-32bb-499e-8839-cc529a4af7f1","owner":[],"postedDate":"August 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-28T03:23:15+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-07 11:34:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7188073","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7188073","identity":"rs-7188073","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}