{"paper_id":"4e08ff2c-8533-4937-9c43-b059c92e10ea","body_text":"Genomic Insights and Biogeography of Endemic Galapagos Geckos: Unraveling Population Structure and Species Delimitation Across Human-Inhabited Islands | 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 Article Genomic Insights and Biogeography of Endemic Galapagos Geckos: Unraveling Population Structure and Species Delimitation Across Human-Inhabited Islands Gabriela Pozo, Juan José Guadalupe, María José Pozo, Diego F. Cisneros-Heredia, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5703179/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted You are reading this latest preprint version Abstract Islands offer invaluable opportunities for studying evolutionary processes due to their isolation and distinct environmental conditions. The Galapagos Islands, renowned for their rich biodiversity, host several endemic gecko species of the genus Phyllodactylus (Gekkota: Phyllodactylidae). Despite their importance derived from their specialized adaptations and their crucial role in maintaining ecosystem balance, few studies have been conducted on these geckos. This highlights the need for comprehensive genomic research to understand their evolutionary patterns and population dynamics. This study elucidates the genetic diversity and population structure of six endemic Phyllodactylus species found on four human-inhabited islands in the Galapagos using a RAD-Seq approach. The analysis of over 30,000 loci from 93 individuals revealed five distinct genetic clusters, corresponding to P. baurii, P. galapagensis, P. darwini, P. leei , and a combined cluster of P. simpsoni and P. andysabini . Our results indicate that P. galapagensis clusters with the combined P. simpsoni - P. andysabini group, while P. baurii shows close genetic relationships with both clusters, in accordance with the obtained phylogeny and the sequential emergence of the Galapagos Islands where each species is found. Substantial genetic differentiation was observed between species, with high F ST and D XY values. However, our analyses indicate that gecko populations from across Isabela and Fernandina islands exhibit very low genetic differentiation, leading us to propose the synonymization of P. andysabini with P. simpsoni . Within-species population structure was associated with geographic barriers and gene flow restrictions. Surprisingly, human activity does not appear to be causing significant admixture among these populations; instead, population boundaries remain intact, indicating that geographic or behavioral barriers are stronger than human influences in limiting gene flow. Overall, we found low genetic diversity across species, probably due to their endemic nature and island isolation. This genomic study provides insights into the evolutionary dynamics shaping these unique geckos and highlights the importance of employing high-resolution genomic tools in insular ecosystems for their effective conservation and management. Biological sciences/Ecology/Biogeography Biological sciences/Genetics/Population genetics Biological sciences/Genetics/Population genetics/Genetic variation Galapagos Islands geckos Phyllodactylus Genetic diversity Population structure RAD-seq Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Islands offer invaluable opportunities for understanding evolutionary processes due to their isolation and distinct environmental conditions [ 1 , 2 ]. Two important factors when studying evolutionary processes on islands are oceanic and topographic barriers. In volcanic islands, eruption events and landslides can produce habitat fragmentation and isolate populations, driving genetic differentiation and speciation within islands [ 3 ]. Nonetheless, patterns of genetic differentiation between populations from different islands and populations within the same island suggest oceanic barriers are more effective than topographic barriers at promoting isolation in islands [ 4 , 5 ]. The Galapagos Islands are renowned for their ecological significance and unique biodiversity. This volcanic archipelago located approximately 1,000 km off the coast of Ecuador serves as a natural laboratory for understanding mechanisms of adaptation and speciation [ 6 , 7 ]. The fauna of the Galapagos Islands includes several endemic gecko species. Geckos are one of the most diverse clades of lizards, with a worldwide distribution and a high diversity in the tropics. Many gecko clades have dispersed and diversified in island ecosystems due to their ability to traverse wide barriers [ 8 ]. Geckos in island ecosystems have unique phenotypes due to the evolutionary processes product of their geographic isolation, which can profoundly impact their genetic structure, also influenced by intraspecific competition [ 9 – 11 ]. Understanding their genetic diversity within these island ecosystems is crucial for conserving their unique biodiversity [ 3 ]. The Galapagos Islands are home to eleven endemic species of leaf-toed geckos of the genus Phyllodactylus (family Phyllodactylidae) [ 12 , 13 ]. Additionally, four species of non-native geckos have arrived in the Galapagos over the last two centuries and established populations in human-inhabited islands (family Gekkonidae: Hemidactylus frenatus and Lepidodactylus lugubris ; Phyllodactylidae: Phyllodactylus reissii ; and Sphaerodactylidae: Gonatodes caudiscutatus ) [ 14 – 17 ]. While large reptiles, such as giant tortoises, are among the best-studied inhabitants of the Galapagos [ 18 – 21 ], information about the evolutionary patterns, species diversity, biogeography, and ecological dynamics of smaller reptiles like the Galapagos leaf-toed geckos and Galapagos racer snakes remain unexplored, and the impacts caused by non-native species on their populations have yet to be understood [ 13 , 22 ]. Galapagos leaf-toed geckos are primarily nocturnal, foraging on the ground, rocky crops, tree trunks, or buildings, and seeking shelter during the day under rocks, tree trunks, wood, lava blocks, and cactus stumps [ 23 – 26 ]. Six of the eleven endemic species of leaf-toed geckos occur on human-inhabited islands: Phyllodactylus andysabini from Isabela Island, Phyllodactylus baurii from Floreana Island, Phyllodactylus leei and P. darwini from San Cristobal Island, Phyllodactylus galapagensis from Santa Cruz Island, and Phyllodactylus simpsoni from Isabela [ 13 , 26 ]. P. simpsoni is also found on Fernandina Island, which is an uninhabited island. Phyllodactylus andysabini and P. simpsoni are allopatric in Isabela Island, with P. andysabini restricted to the northern part of the island, while P. simpsoni occurs across central and southern regions. Only two of these species occur in sympatry, P. leei and P. darwini , both inhabiting San Cristobal Island. However, they are easily differentiated by their body size, with P. darwini being the largest endemic gecko in the archipelago [ 26 ]. These geckos face threats such as habitat change and loss, as well as impacts from introduced species that may act as predators, competitors, or carriers of diseases and parasites [ 24 , 25 , 27 , 28 ], similar to what has happened to endemic gecko populations on other tropical islands [ 29 – 36 ]. Endemic species hold significant ecological and evolutionary importance, due to their highly specialized adaptations to unique environments, making them key indicators of ecosystem health and resilience. Their restricted geographic ranges and high vulnerability to environmental changes underscore their critical role in conservation efforts to preserve biodiversity and maintain ecosystem balance [ 37 ]. Despite this, there are few genetic studies on Phyllodactylus species native to Galapagos, and to our knowledge, no genomic studies have been reported to date. Existing genetic research on the Galapagos leaf-toed geckos has provided valuable insights into their evolutionary history and diversity, predominantly focusing on understanding the biogeographic patterns of the genus and its historical colonization dynamics within the archipelago [ 38 – 40 ]. Notably, studies from 2014 and 2016 by Torres-Carvajal et al. used nuclear and mitochondrial markers to shed light on the evolutionary history and diversification of the Phyllodactylus genus from Galapagos and test colonization hypothesis [ 13 , 38 ]. Another study used nuclear and mitochondrial markers to describe two new species from Isabela Island and presents an updated molecular phylogenic hypothesis of the genus Phyllodactyus in the Galapagos [ 23 ]. However, there is a need for more comprehensive genomic studies that can provide a deeper understanding of the mechanisms driving diversification and shaping the genetic diversity and population structure of Galapagos leaf-toed geckos. The aim of this study was to understand the genetic diversity and population structure of the six endemic Galapagos gecko species that are found on human-inhabited islands using RAD-Seq (Restriction Site Associated DNA Sequencing), which has proven to be a powerful method for understanding population dyanimcs and evolutionary processes in various organisms [ 41 , 42 ]. Our results reveal clearly defined species boundaries, with one notable exception, alongside robust population structure. Our results reveal well-defined species boundaries, with one notable exception, alongside a robust population structure apparently not influenced by anthropogenic factors, and low levels of genetic diversity. These findings offer valuable implications for informing conservation strategies, especially given the significant changes currently taking place in the Galapagos Islands as a result of human activities. 2. Results 2.1 RAD-seq A total of 95 DNA samples were processed for RAD-seq analysis in the present study. RAD-seq yielded a total of 1,021,167,325 forward reads and an equivalent number of reverse reads (Supplementary Table S1 ). None of the sequences were flagged as poor quality. The sequence length for both files is uniform at 169 base pairs, which is consistent with the size selection performed for sequencing. The GC content differs slightly between the forward and reverse reads, with percentages of 49% and 48%, respectively. Notably, the mean sequence quality, as indicated by Phred scores, remains consistent across both the forward and reverse reads files, with a quality score of 36. 2.2 Population Structure and Genetic Differentiation After processing through Stacks and VCFtools a final data set of 93 samples (two samples were eliminated, one due to low coverage and one due to high missing data, see methods) and 30,353 loci were used for population structure and genetic differentiation analyses. Figure 1 A illustrates the distribution of samples across Fernandina, Isabela, Santa Cruz, Floreana and San Cristobal islands. The principal component analysis (PCA) shows the differentiation between the 93 samples of Phyllodactylus species studied. PC1(28%) vs. PC2 (23%) reveals three distinct clusters (Fig. 1 B). P. darwini comprises the first cluster, P. leei forms the second cluster, while P. baurii, P. galapagensis, P. simpsoni , and P. andysabini are grouped in the third cluster. PC1(28%) vs. PC3 (14%) further separates the data distinguishing P. baurii from P. galapagensis, P. simpsoni , and P. andysabini (Fig. 1 C). The unrooted phylogenetic tree (Fig. 2 A) elucidates the interrelationship among the sampled specimens, separating all Phyllodactylus species, except for P. andysabini , which is nested within the branch of P. simpsoni . Species are clustered according to their geographic location across the islands (Supplementary Table S2). The haplotype genealogy (Fig. 2 B) grouped the six analyzed species into five distinct clusters. In accordance with the results from the phylogenetic tree, the five clusters correspond to different Phyllodactylus species and P. andysabini is found within the P. simpsoni cluster. F ST estimates ranged from 0.524 to 0.981 (Fig. 3 A). The lowest genetic divergence (F ST = 0.524) was found between P. galapagensis and the combined P. simpsoni / P. andysabini group. P. darwini presented high values of genetic divergence with the other species, being the highest with P. baurii (F ST = 0.961). The D XY analysis between the six Phyllodactylus species generated values ranging from 0.02 to 0.117 (Fig. 3 B). The most closely related species, P. andysabini and P. simpsoni , showed the lowest value (D XY = 0.02), while the most genetically distinct species were P. darwini and P. baurii (D XY = 0.117). In Fig. 4 , FST values were calculated among individuals from the different collection sites of a species on each island (see Supplementary Table S3 for details of sampling locations within each island). Specifically, Fig. 4A1 and 4A2 corresponds to comparisons of P. leii and P. darwini sampling locations in San Cristobal, respectively. Figure 4 B depicts the genetic distances between P. galapagensis sampling locations in Santa Cruz, Fig. 4 C shows P. baurii genetic distances in Floreana, and Fig. 4 D represents the genetic distances within P. simpsoni and P. andysabini sampling locations in Isabela and Fernandina Islands. The F ST values follow a pattern corresponding to geographical distances, with the lowest values found in the closest collection sites, and the values increasing as the distances between sampling locations increase. For example, in Fig. 4 C, P. baurii sampling locations exhibited a low F ST value (0.04) between the west and north sampling locations (which are closer geographically) and a higher value (0.102) between the west and east sampling locations (which are farther apart). However, a Mantel test confirmed a significant correlation between geographic and genetic distances only for P. galapagensis sampling locations on Santa Cruz Island (Figs. 4 B and 4 E, p-value = 0.0001). 2.3 Population Size and Genetic Diversity P. baurii and P. darwini exhibited the lowest values of expected heterozygosity (He), with 0.0175 and 0.0189, respectively, followed by P. andysabin i with 0.0425. P. leei and P. galapagensis displayed higher values (0.0507 and 0.0595, respectively), and P. simpsoni had the highest He value (0.0794) (Table 1 ). Nucleotide diversity values displayed the same pattern: P. darwini and P. baurii showed the lowest values of nucleotide with values of 0.0023 and 0.0047, respectively, followed closely by P. andysabini with a value of 0.0066. P. leei and P. galapagensis exhibited values of 0.0161 and 0.0168, respectively, and P. simpsoni showed the highest nucleotide diversity (0.0225). Table 1 Genetic diversity parameters, expected heterozygosity (He) and nucleotide diversity (π), for the 93 Phyllodactylus individuals studied. Heterozygosity (He) and Nucleotide diversity (π) P. simpsoni P. baurii P. leei P. darwini P. galapagensis P. andysabini He 0.0794 0.0175 0.0507 0.0189 0.0595 0.0425 π 0.0225 0.0047 0.0161 0.0023 0.0168 0.0066 3. Discussion Our study employed a comprehensive genomic approach, analyzing over 30,000 loci, and was able to elucidate the population structure and genetic differentiation among Phyllodactylus species inhabiting human-populated islands in the Galapagos. This high-resolution analysis provided valuable insights into the genetic diversity within and between species, revealing distinct genetic clusters, challenging previous species classifications, and highlighting patterns of genetic diversity and differentiation. Genetic clusters According to the results obtained in the PCA (Fig. 1 ), the phylogenetic tree (Fig. 2 A) and the haplotype network (Fig. 2 B), five distinct genetic clusters corresponding to P. baurii , P. galapagensis , P. darwini , P. leei , and a combined cluster for P. simpsoni and P. andysabini were revealed. These findings confirm that P. baurii, P. galapagensis , P. darwini , and P. leei are clearly defined species, as suggested by the literature [ 38 , 39 ]. This is expected since most of these species are found on different islands, allowing them to evolve in isolation [ 6 , 43 , 44 ]. Aside from P. simpsoni and P. andysabini which will be discussed further on, P. darwini and P. leei are the only species in this study that occur in sympatry on the same island, however they are distinctly separated from each other e (Figs. 1 and 2 ). This difference could be attributed to the more recent colonization of the island by the ancestor of P. darwini , which is estimated to have occurred around 3 million years ago. In contrast, evidence suggests that the ancestor of the other Phyllodactylus species in the Galapagos colonized the islands 13 million years ago, and since then these species have been isolated from their continental relatives [ 38 ]. Additionally, the two species are phenotypically distinct, with P. darwinii having a much larger body size compared to P. leei , as well as a different scalation pattern and coloration [ 45 ]. The substantial size difference between these species, together with their disparate colonization times, likely facilitated the co-existence of these two distinct species on the same island by reducing competition for resources through niche partitioning [ 6 , 46 ]. The PCA (Fig. 1 ) shows the P. galapagensis cluster in close proximity to the P. simpsoni - P. andysabini combined cluster, while the phylogenetic tree and haplotype network (Fig. 2 ) separate these clusters into two clearly defined groups. These findings are consistent with the historical classification of P. simpsoni and P. andysabini as part of P. galapagensis , and their more recent phylogenetic divergence [ 23 , 38 ]. Additionally, the P. baurii cluster is closely related to the P. galapagensis and P. simpsoni - P. andysabini clusters, reflecting their phylogenetic relationships as reported by previous genetic studies [ 38 , 39 ]. These results also reflect the chronological formation of the extant islands in the archipelago which are reported to have emerged in three distinct groups. San Cristóbal, where P. leei occurs, arose around 2.5 million years ago along with Española. Santa Cruz (home to P. galapaguensis ), and Floreana ( P. bauri ) formed between 1.5 and 2 million years ago, along with the rest of the central islands. Finally, Isabela and Fernandina, where the P. simpsoni–P. andysabini group is found, emerged about 0.5 million years ago [ 47 , 48 ]. P, simpsoni and P. andysabini as a single species The results of the D XY (Fig. 3 B), PCA (Fig. 1 ), phylogenetic tree (Fig. 2 A) and haplotype network (Fig. 2 B) collectively support the notion that P. simpsoni and P. andysabini may not be separate species, contrary to the previous classification by Arteaga et al. (2019) who diagnosed them based on morphological traits and five genetic markers [ 23 ]. Our study, utilizing over 30,000 loci, provides strong evidence that P. andysabini and P. simpsoni are likely conspecific, which is supported by their shared habitat on Isabela Island and corroborated by previous genetic studies [ 38 , 39 ]. It is noteworthy that the D XY value, which reflects the minimum nucleotide differences between the two species, is close to 0, which reinforces their genetic similarity and suggesting conspecificity [ 49 ]. Arteaga et al. (2019) proposed two phenetic differences between P. simpsoni and P. andysabini in their original description: the absence of supranasal contact and the presence of a densely stippled throat in P. andysabini [ 23 ]. However, individuals of P. simpsoni also were reported to exhibit these characteristics (43% individuals of P. simpsoni examined by Arteaga et al. (2019) had absence of contact between supranasals and 36% had a brown stippled throat) [ 23 ]. Our data agree that these two characters are present in populations currently assigned to P. simpsoni . Therefeore, these morphological characters are not reliable discriminators. High-resolution RAD-Seq data support that all studied populations of Isabela and Fernandina Islands correspond to a single species. This technique has proven to be a powerful tool for detecting population structure and evolutionary patterns in species due to the use of a much larger number of loci than traditional markers, as well as the high depth of sequencing coverage it provides [ 50 , 51 ]. Therefore, we propose the synonymy of Phyllodactylus andysabini Arteaga, Bustamante, Vieira, Tapia, Carrión & Guayasamin, 2019 with Phyllodactylus simpsoni Arteaga, Bustamante, Vieira, Tapia, Carrión & Guayasamin, 2019, making P. simpsoni the valid name for all gecko populations from Isabela and Fernandina islands. Genetic differentiation between and within species The F ST and D XY values found in this study revealed a significant differentiation between species, with F ST values ranging between 0.524 and 0.981 and D XY values between 0.02 and 0.117 (Fig. 3 ). With the exception of P. andysabini and P. simpsoni , these high values indicate clearly differentiated species [ 49 ]. Interestingly, the genetic differentiation between P. darwini and all other species is higher than the values found between all other species (Fig. 3 ). As mentioned previously, this could be due to the fact that P. darwini is the result of a separate, more recent colonization event, and thus more genetically distinct from all the other species that derived from a single colonization event [ 38 ]. Additionally, the genetic differentiation values seem to be consistent with the island formation age: species from older islands tend to have higher genetic differentiation values [ 47 , 48 , 52 ]. When analyzing the F ST values within P. simpsoni , the highest value was found between the samples from the islands of Fernandina and Isabela. Despite this, the Mantel test did not yield significant results (Fig. 4 D). It is very likely that the differentiation observed between individuals from these two islands is due to the body of water that separates them, since this acts as a barrier to gene flow, generating isolation and genetic differentiation between sampling locations from different islands [ 53 ]. F ST values within P. baurii , P. leii and P. darwini species were low, although a trend could be observed: individuals from opposite ends of each island were more genetically differentiated (Fig. 4 ). However, the Mantel test was not significant, indicating no correlation between geographic distance and genetic divergence within these species. This could be due to the volcanic nature of these islands. Eruption events and landslides are phenomena that promote habitat fragmentation and genetic isolation, thereby driving speciation as well as differentiation within species living on the same island [ 3 ]. Regarding P. galapagensis , a clear difference was observed between northern and southern sampling locations, and the Mantel test indicated that this divergence can be attributed to geographic distances. This suggests that geographic distance could indeed play a role in shaping genetic differentiation within sampling locations of the same species [ 54 , 55 ]. Anthropogenic impacts are an important factor to consider when studying population differentiation and divergence in the islands. Human activity on islands like San Cristobal, Isabella and Santa Cruz has been substantial, including land use changes, tourism, and urbanization, which can fragment habitats and alter ecosystems [ 56 , 57 ] Despite this, notable genetic diversity and structure remain among gecko populations, suggesting resilience or isolated gene pools. Surprisingly, humans do not appear to be causing significant admixture among these populations; instead, population boundaries remain intact, suggesting that geographic or behavioral barriers are stronger than the influences of human activity in preventing gene flow. Conducting a detailed geographic analysis of sampling sites could provide further insights into how human activities and landscape features may be shaping or isolating gecko diversity, potentially indicating which populations are more vulnerable to future changes and highlighting conservation priorities [ 56 ]. Genetic diversity The expected heterozygosity (He) values for Phyllodactylus species endemic to the Galapagos Islands ranged from 0.0175 ( P. baurii ) to 0.0794 ( P. simpsoni ); while nucleotide diversity ranged from 0.0023 ( P. darwini ) to 0.0225 ( P. simpsoni ) (Table 1 ). Specific indicators of genetic diversity have not been calculated for other species within the Phyllodactylus genus before this study, however research on gecko species has revealed varying levels of genetic diversity. For instance, in Gekko japonicus , Wei et al. (2015) found a mean expected heterozygosity of 0.395 to 0.797 in one population from Wenzhou, Zhejiang Province, China [ 51 ], while Li et al. (2007) reported a range of 0.584 to 0.917 in different microsatellite markers in seven populations of Gekko swinhonis from China [ 58 ]. It is important to note that firstly, these species are not island species, therefore the genetic diversity values obtained may not be comparable to our study group. Secondly, these studies were done using microsatellite markers, which takes into account few loci (usually less than 20) compared to the thousands of loci analyzed using RAD-Seq. Microsatellites studies that chose only polimorphic loci can overestimate genetic diversity [ 59 ], and are not ideal for reflecting genome-wide genetic diversity [ 60 ]. In contrast, several studies have shown that techniques such as RAD-Seq are powerful tools for detecting genetic diversity [ 61 , 62 ]. The relatively low genetic diversity found in the species of this study can be attributed to their endemic nature, as they are confined to a single island or, in the case of P. simpsoni , two islands. Endemic island species often exhibit lower genetic diversity due to various factors associated with their unique evolutionary history and the challenges posed by insular environments [ 63 – 66 ]. These species are characterized by reduced genetic variation, which can negatively impact their overall fitness and increase their susceptibility to extinction [ 64 ]. Recent population bottlenecks, rather than the lasting effects of island colonization alone, may have further contributed to the diminished genetic diversity[ 63 ]. Thus, the possible effect of these factors, including bottlenecks, limited gene flow and distinctive evolutionary trajectories of island species, have probably played an important role in the genetic makeup of these endemic species, leading to reduced genetic diversity. Within the studied species, P. baurii and P. darwini showed the lowest nucleotide diversity and expected heterozygosity values (Table 1 ). In the case of P. baurii , this presumably reflects the constraints imposed by its restricted geographic distribution [ 67 , 68 ]. Floreana, the island where this gecko species is found, has a relatively small area of 173 km2. On the other hand, the low genetic diversity values observed in P. darwini could be explained by its relatively recent colonization history, occurring only 3 million years ago, which contrasts with the much older colonization events of other endemic Phyllodactylus species in the archipelago, dating back 13 million years [ 38 ]. The lower genetic diversity we observed may reflect a more recent founder effect [ 69 – 71 ]. In all cases, the low nucleotide diversity and expected heterozygosity values (Table 1 ) may be further influenced by ongoing evolutionary pressures imposed by human activities [ 72 ]. These pressures include the presence of introduced predators like cats and rats, which exert predatory pressure on gecko species, as well as competition and predation from introduced gecko species in the archipelago that cohabit in some places with native species [ 73 , 74 ]. Human habitat modifications might have also contributed to exacerbate the low genetic diversity observed in the species analyzed in this study [ 75 – 77 ]. 4. Conclusion Our findings revealed clearly defined genetic clusters for five of our studied species: P. darwini, P. baurii, P. simpsoni, P. galapagensis and P. leei . We also observed population structure within species, likely influenced by land barriers such as volcanoes andan ocean barrier restricting gene flow. Our analyses led us to conclude that P. simpsoni and P. andysabini exhibit very low genetic differentiation, leading us to propose their synonymization. The genetic relationships among species align with the chronological emergence of the Galápagos islands, suggesting that species diversification followed the island formation sequence. Additionally, while human activities such as land use changes, tourism, and urbanization have impacted islands like San Cristóbal, Isabela, and Santa Cruz, these activities appear to have limited influence on gene flow among gecko populations. The observed population boundaries seem to remain intact, likely due to strong geographic or behavioral barriers. A more detailed geographic analysis of sampling sites could further clarify how these factors contribute to genetic isolation and identify populations vulnerable to future environmental changes. As expected for endemic insular species mostly restricted to a single island, genetic diversity was found to be low across all studied species. P. darwini displayed the highest genetic differentiation from other species, possibly due to its more recent colonization. This species, along with P. baurii , exhibited the lowest genetic diversity. The reduced diversity in P. baurii is likely attributable to its small geographic distribution, while the low diversity in P. darwini may be a result of a more recent founder effect. Our research findings highlight the importance of using high-resolution genomic tools to study genetic variation and population structure in islands. The knowledge gained from this research will not only enhance our understanding of the evolutionary processes shaping these species but also inform conservation strategies aimed at preserving their genetic integrity and ensuring their long-term survival in the face of anthropogenic challenges. 5. Methods 5.1 Sampling Fieldwork was conducted in the Galapagos Archipelago from May to August 2023, in the islands of Santa Cruz, Isabela, Floreana, San Cristóbal, and Fernandina (Fig. 1 ). We collected samples in 27 localities, encompassing urban and natural environments (Table 2 ). We surveyed native gecko species of Phyllodactylus during the day and night, searching in trees, dry logs, under rocks, under tree bark, and other natural and human-made potential refuges. At each site, we captured up to 10 adult individuals of each species present. Table 2 Locations of sampled geckos Species Island Geographic location Ecosystems * Phyllodactylus andisabini Isabela Northwest Lava Phyllodactylus baurii Floreana North, West, and East Deciduous forest, urban area Phyllodactylus darwinii San Cristobal West and East Seasonal evergreen forest, deciduous forest, urban area Phyllodactylus galapagensis Santa Cruz North, East, and South Deciduous forest, urban area Phyllodactylus leei San Cristobal North and South Deciduous forest Phyllodactulus simpsoni Fernandina Northeast Lava Isabela West, East, and South Deciduous forest, lava, urban area * Classification of ecosystems follows the proposal by Rivas-Torres et al. (2018) We collected 184 tail-tip tissue samples from endemic Phyllodactylus individuals for genetic analyses (Supplementary Table S3). 5.2 DNA Extraction and RAD-Sequencing Genomic DNA was extracted from animal tails using a commercial DNeasy Blood & Tissue kit (Qiagen) following manufacturer's instructions with modifications: we repeated each wash steps with buffers AW1 and AW2, and DNA was eluted in a final volume of 34 ul. DNA concentration was measured using Qubit 3 (Thermo Fisher Scientific, USA), and DNA quality was assessed using a Nanodrop 2000 Spectrophotometer (Thermo Fisher Scientific, USA). DNA integrity was analyzed on a 1.5% agarose gel. Samples were normalized to meet Floragenex (Eugene, OR, USA) requirements. The DNA concentration and quality for each of the samples that were sent to Floragenex is shown in Supplementary Table S4. The values of DNA concentration among all samples ranged from 8,92 to 25,8 ng/ul. Few samples showed quality ratios outside of the expected range (1,8 − 2,0). Supplementary Figure S1 illustrates the integrity of DNA samples through agarose gel electrophoresis, where distinct bands indicate the presence of high-quality, non-degraded DNA molecules, suitable for library preparation and sequencing. 95 samples were selected for sequencing, considering the quantity and quality of DNA and the representativeness of the sample distribution in and between islands (Supplementary Table S4). RAD-Seq was conducted by Floragenex (Eugene, OR, USA) following standard protocols. Genomic DNA underwent quality assessment and quality control (QA/QC) measures before library preparation. The RAD libraries were constructed using the SbfI restriction enzyme. Following restriction, fragments of 169 base pairs were selected for sequencing. Sequencing of the RAD-Seq libraries was carried out using the Illumina NovaSeq6000 platform. The sequencing runs were performed with paired-end reads of 150 base pairs, employing the NovaSeq6000 S Prime 300 cycle kit (Sp300). Both lanes of the Sp300 flow cell were allocated exclusively for sequencing. The sequencing data were provided in fastq format for downstream analysis. 5.3 Read processing and creation of loci catalogue using Stacks Forward and reverse sequencing reads were analyzed using FastQC [ 78 ]. We then used Stacks v2.65 to filter reads and create a loci catalogue for our population structure and genetic diversity analyses. Specifically, we began using process_radtags to demultiplex and clean the reads, specifying barcode-dist-1 of 3 to allow three mismatches when rescuing single-end barcodes, -c/--clean to remove reads with uncalled bases, -q/--quality to discard low-quality reads, and -r/--rescue to rescue barcodes and cut sites. This approach retained over 80% of the reads. After demultiplexing we ran the main Stacks pipeline consisting of ustacks (builds loci), cstacks (creates a catalog of loci), sstacks (matches samples against the catalog), gstacks (assembles paired-end contigs, calls variant sites, and genotypes samples), and populations (filters data, calculates population genetics statistics, and exports various data formats) [ 79 ]. Following the recommendations of Catchen et al. (2013) [ 79 ], Paris et al. (2017) [ 80 ] and Rivera-Colón & Catchen (2022) [ 81 ], and based on the scripts found in Cerca et al. (2021a) [ 82 ], we ran the aforementioned Stacks pipeline using the wrapper program denovo_map.pl, since no reference genome is available for Phyllodactylus species. The populations were delineated according to our population map (list of our 95 Phyllodactylus samples). We optimized the parameters -M (maximum nucleotide mismatches allowed between stacks to be merged into a locus) and -n (maximum nucleotide mismatches allowed between stacks during the construction of the catalog) within the ustacks and cstacks modules of the Stacks pipeline [ 79 , 80 ], by exploring a range of values from 1 to 7 for both parameters. Subsequently, we analyzed the cumulative count of loci resulting from various combinations of -M and -n values to identify the inflection point at which the change in the count of -R80 loci (number of polymorphic loci present in at least 80% of the samples) approached zero. The combination of -M 3, -n 3, and -R 80 was determined as the optimal parameter set for the de novo assembly of loci within the Phyllodactylus sp. dataset. We followed the methodology outlined by Cerca et al. (2021b) to exclude samples and loci exhibiting a high degree of missing data[ 83 ]. Samples displaying a mean depth of coverage less than 35 x (individuals 3961 P. galapagensis and 4140 P. darwini )) were removed utilizing VCFtools v.0.1.5 with the --mean_depth flags [ 84 ]. Additionally, we used VCFtools to further filter dataset, by applying the following filters: a mean coverage depth between 15 and 200 (--min-meanDP 15 --max-meanDP 200) [ 84 ]. Finally, 93 out of 95 samples and 30,353 loci were retained for subsequent genetic diversity and phylogenetic analyses. 5.4 Population structure analyses Principal component analysis (PCA) was conducted to assess the genetic variation between the 93 samples of Phyllodactylus species using the R package adegenet [ 85 ] following the PCA script of Cerca et al. (2021a) [ 82 ]. Before running the PCA we used the option ‘--write-random-snp’ in the populations program to diminish linkage disequilibrium in the dataset. Using the program vcf2phylip.py with the –nexus flag [ 86 ], we derived a PHYLIP file from the dataset comprising all available sites. Then, we employed IQ-TREE v1.6.12 [ 87 – 89 ] to infer the phylogenetic relationships among the 93 individuals. The analysis uses the General Time Reversible (GTR) model, incorporating an ascertainment bias (ASC) correction option (-m GTR + ASC), and included 1,000 bootstrap replicates to determine bootstrap support (BS) values [ 88 ]. The resultant phylogenetic tree was generated with the Newick tree format code outputted by IQ-TREE and employing the ape package in R for visualization [ 90 ]. Finally, we constructed a haplotype genealogy graph using the Fitchi algorithm [ 91 ] with the parameters -m 0.3 and -p auto , aiming to elucidate the transitions and transversions between the sampled sequences. We evaluated the extent of genetic differentiation among Phyllodactylus species by computing Weir and Cockerham’s F ST [ 92 ] using VCFtools [ 84 ]. Here, P. simpsoni is grouped with P. andysabini due to their genetic similarity and to ensure a minimum of five samples for F ST comparisons (as five individuals per group is the minimum number normally used for pairwise F ST calculations). Interspecies differentiation D XY analyses were performed to offer supplementary evidence of genetic divergence, employing the Fitchi algorithm [ 91 ]. To understand the genetic differentiation between sampling locations within species, we performed F ST analysis using VCFtools using Weir and Cockerham’s F ST [ 84 ]. For P. galapagensis and P. baurii , we calculated pairwise F ST for each sampling location, as there were at least five individuals per location. For the other species, PCAs were conducted for each species. If there were discernible clusters (i.e. the individuals formed clear, delimited groups in the PCA), the individuals were grouped according to the clusters for F ST calculations. When there were no discernible clusters, individuals were grouped according to their geographic regions (i.e. North, South, East, West or Center of the island) (see Supplementary Table S3). A Mantel test was conducted to assess spatial correlation among the species, utilizing the adegenet package in R [ 85 ]. The first matrix used for the Mantel test consisted of the F ST matrix within each species. For the second matrix, we employed one geographic coordinate per location (for grouped Phyllodactylus individuals) (see Supplementary Table S3). 5.5 Calculation of genetic diversity To understand the genetic diversity among species, we computed the expected heterozygosity (He) using the populations software in Stacks 2.65 [ 79 ]. Additionally, we calculated nucleotide diversity (π) using the Fitchi algorithm [ 91 ]. Declarations Competing interests The authors declare no competing interests. Funding This research was funded by Galápagos Conservancy under the grant number Galápagos Conservancy USFQ 1 , as part of a partnership between Galápagos Conservancy and Universidad San Francisco de Quito (USFQ). Author Contribution M.L.T.: conceptualization, supervision, methodology, writing—review and editing. G.P.: methodology, investigation, formal analysis, writing—original draft, writing—review and editing. D.C.-H.: conceptualization, funding acquisition, writing—review and editing. J.J.G., M.J.P.: investigation, writing—original draft, writing—review and editing. J.C.: formal analysis, writing—review and editing. P.A.-B., M.V.S: formal analysis, writing—original draft. M.D.-J.: sample collection, writing—original draft, writing—review and editing. E.P.-R., D.B.-Z., D.V.: writing—original draft. Acknowledgement The authors would like to thank Verónica Baquero, Pamela Borja and Daniel Dávila for their contributions to the DNA extractions in this project. We thank the Galápagos National Park Directorate, including Galo Quezada, Daniel Lara, Jorge Carrión, Carlos Vera, and all authorities and park rangers of the Galapagos National Park for their valuable comments during project proposal reviews and support with logistics and transportation to the sampling sites. Special thanks to Carlos Mena, Sofía Tacle, Leandro Vaca, Cecibel Narváez, Anita Carrión, Sylvia and Jessenia Sotamba, Juan Pablo Muñoz, Marjorie Riofrío, Daniela Alarcón, Paola Carrión, Cristina Vintimilla, Máximo, and Marlene Ochoa, and all the personnel from the Galapagos Science Center GSC (Universidad San Francisco de Quito USFQ and University of North Carolina at Chapel-Hill UNC) and Universidad San Francisco de Quito, GAIAS Galapagos extension for their constant support and help. We acknowledge the GSC for providing access to equipment, labs, and other facilities. 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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-5703179\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":405695462,\"identity\":\"f5807993-89a3-4d67-9cb6-37e85b50ed38\",\"order_by\":0,\"name\":\"Gabriela Pozo\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Laboratorio de Biotecnología Vegetal, Universidad San Francisco de Quito USFQ\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Gabriela\",\"middleName\":\"\",\"lastName\":\"Pozo\",\"suffix\":\"\"},{\"id\":405695463,\"identity\":\"129cf54d-9e17-4f7f-82a1-c52ff47fb8d1\",\"order_by\":1,\"name\":\"Juan José Guadalupe\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Laboratorio de Biotecnología Vegetal, Universidad San Francisco de Quito USFQ\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Juan\",\"middleName\":\"José\",\"lastName\":\"Guadalupe\",\"suffix\":\"\"},{\"id\":405695464,\"identity\":\"951159e5-ba40-417e-8972-216d7019b0b3\",\"order_by\":2,\"name\":\"María José Pozo\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Laboratorio de Biotecnología Vegetal, Universidad San Francisco de Quito USFQ\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"María\",\"middleName\":\"José\",\"lastName\":\"Pozo\",\"suffix\":\"\"},{\"id\":405695465,\"identity\":\"8722b26f-ddb4-49ea-ba5c-ebbe391a1525\",\"order_by\":3,\"name\":\"Diego F. Cisneros-Heredia\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Laboratorio de Zoología Terrestre, Instituto de Biodiversidad Tropical IBIOTROP, Universidad San Francico de Quito USFQ\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Diego\",\"middleName\":\"F.\",\"lastName\":\"Cisneros-Heredia\",\"suffix\":\"\"},{\"id\":405695466,\"identity\":\"8ed5004b-730c-4da6-8150-4ce543edf2f1\",\"order_by\":4,\"name\":\"José Cerca\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Department of Biosciences, Centre for Ecological and Evolutionary Synthesis (CEES), University of Oslo\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"José\",\"middleName\":\"\",\"lastName\":\"Cerca\",\"suffix\":\"\"},{\"id\":405695467,\"identity\":\"bf965940-d95f-4ed7-9453-9abbbfac8219\",\"order_by\":5,\"name\":\"Pablo Alarcón-Bolaños\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Laboratorio de Biotecnología Vegetal, Universidad San Francisco de Quito USFQ\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Pablo\",\"middleName\":\"\",\"lastName\":\"Alarcón-Bolaños\",\"suffix\":\"\"},{\"id\":405695468,\"identity\":\"2f79895e-d2b4-4601-85f4-9407877cf0b6\",\"order_by\":6,\"name\":\"María Victoria Suárez\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Laboratorio de Biotecnología Vegetal, Universidad San Francisco de Quito USFQ\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"María\",\"middleName\":\"Victoria\",\"lastName\":\"Suárez\",\"suffix\":\"\"},{\"id\":405695469,\"identity\":\"0b83981e-981f-48dd-a376-b1f22e7ba1b1\",\"order_by\":7,\"name\":\"Mateo Dávila-Játiva\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Laboratorio de Zoología Terrestre, Instituto de Biodiversidad Tropical IBIOTROP, Universidad San Francico de Quito USFQ\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mateo\",\"middleName\":\"\",\"lastName\":\"Dávila-Játiva\",\"suffix\":\"\"},{\"id\":405695470,\"identity\":\"39654fd7-72c6-4a0c-987a-05659bbefbc2\",\"order_by\":8,\"name\":\"Emilia Peñaherrera-Romero\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Laboratorio de Zoología Terrestre, Instituto de Biodiversidad Tropical IBIOTROP, Universidad San Francico de Quito USFQ\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Emilia\",\"middleName\":\"\",\"lastName\":\"Peñaherrera-Romero\",\"suffix\":\"\"},{\"id\":405695471,\"identity\":\"0f57e779-94a6-4ca1-bdde-7464305b1226\",\"order_by\":9,\"name\":\"David Brito-Zapata\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Laboratorio de Zoología Terrestre, Instituto de Biodiversidad Tropical IBIOTROP, Universidad San Francico de Quito USFQ\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"David\",\"middleName\":\"\",\"lastName\":\"Brito-Zapata\",\"suffix\":\"\"},{\"id\":405695472,\"identity\":\"9e001007-8de8-474a-822d-754327684e07\",\"order_by\":10,\"name\":\"Daniel Velasco\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Laboratorio de Zoología Terrestre, Instituto de Biodiversidad Tropical IBIOTROP, Universidad San Francico de Quito USFQ\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Daniel\",\"middleName\":\"\",\"lastName\":\"Velasco\",\"suffix\":\"\"},{\"id\":405695473,\"identity\":\"129a89e1-8876-4f90-8e25-0d4d3c5a7b68\",\"order_by\":11,\"name\":\"Maria de Lourdes Torres\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYBACPigtx8DA+ABIMxPWwsYGoY2Bqg1I05LYQLwW+eZjnysq6tI3nD/MeIOhwjqxgb35AQFb2JJnnjlzOHfDjWRmC4Yz6YkNPMcMCGjhMWZsbDsA1MJ/TIKx7XBig0QOIb+AtPyrSzc4f5hNgvEfUIv8G2K0NDAnGBxIBmppANnCQ0hLWjJjw7HDhjNBfkk4lm7cxpOG3y/8zIcPMzbU1MnzgULsQ421bD/74Qf4rUEGEgkge4lXD9JCkupRMApGwSgYMQAAzYM9mzzKUxEAAAAASUVORK5CYII=\",\"orcid\":\"\",\"institution\":\"Laboratorio de Biotecnología Vegetal, Universidad San Francisco de Quito USFQ\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Maria\",\"middleName\":\"de Lourdes\",\"lastName\":\"Torres\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-12-24 03:53:04\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-5703179/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-5703179/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1038/s41598-025-24790-2\",\"type\":\"published\",\"date\":\"2025-11-20T15:58:18+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":75178489,\"identity\":\"7a522407-acf0-43a7-b13e-d0b1c894f1e6\",\"added_by\":\"auto\",\"created_at\":\"2025-01-31 15:42:25\",\"extension\":\"jpg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":89166,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eClusters of endemic geckos based on principal component analysis (PCA) using 93 \\u003cem\\u003ePhyllodactilus\\u003c/em\\u003e individuals. The geographical distribution of these individuals is depicted across the islands where the samples were collected. A, Distribution map of the 93 analyzed samples. Principal Component Analysis (PCA) scores plot: B. PC1 (28%) vs. PC2 (23%), and C. PC1 (28%) vs. PC3 (14%) evaluating the variability of 30,353 loci. The individuals (dots) are colored according to each species.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Picture1.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5703179/v1/812a84e008f500d9f6a728a5.jpg\"},{\"id\":75178506,\"identity\":\"73c9b838-b262-467a-9a59-09a436ae89d8\",\"added_by\":\"auto\",\"created_at\":\"2025-01-31 15:42:26\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":904307,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003ePhylogenetic tree and a haplotype genealogy graph of the six endemic \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003especies from the Galapagos Islands. A. Phylogenetic tree, the numbers at the top of the branches correspond to different \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e individuals B. Haplotype network. Each individual is represented as a node (colored circles).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5703179/v1/60f35df51a2167327b35e639.png\"},{\"id\":75178508,\"identity\":\"e1ab38aa-b819-4f39-ae90-9cb55c25a1b2\",\"added_by\":\"auto\",\"created_at\":\"2025-01-31 15:42:26\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":192595,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eHeatmap of pairwise divergence measures between Phyllodactylus species. A. FST analysis between the analyzed Phyllodactylus species. P. simpsoni was grouped with P. andysabini for this analysis as described the in Methods section. B. DXY pairwise comparison between the six Phyllodactylus species.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5703179/v1/76978f736b15120da70bd469.png\"},{\"id\":75178773,\"identity\":\"0934f8f4-f73a-4910-9b2d-4f124d719cb5\",\"added_by\":\"auto\",\"created_at\":\"2025-01-31 15:50:27\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":665094,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003ePairwise F\\u003csub\\u003eST\\u003c/sub\\u003e heat map for sampled locations within each species and a Mantel test between geographic and genetic distances. \\u003cstrong\\u003eA.\\u003c/strong\\u003e F\\u003csub\\u003eST\\u003c/sub\\u003e values between sampling locations of \\u003cem\\u003eP. leei\\u003c/em\\u003e (A1), and \\u003cem\\u003eP. darwini\\u003c/em\\u003e (A2). \\u003cstrong\\u003eB.\\u003c/strong\\u003e F\\u003csub\\u003eST\\u003c/sub\\u003e values between sampling locations of \\u003cem\\u003eP. galapagensis\\u003c/em\\u003e. \\u003cstrong\\u003eC.\\u003c/strong\\u003e F\\u003csub\\u003eST\\u003c/sub\\u003e values between sampling locations of \\u003cem\\u003eP. baurii\\u003c/em\\u003e. \\u003cstrong\\u003eD.\\u003c/strong\\u003e F\\u003csub\\u003eST\\u003c/sub\\u003e values between sampling sites of \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e and \\u003cem\\u003eP. andysabini\\u003c/em\\u003e. \\u003cem\\u003eP. simpsoni \\u003c/em\\u003efrom Darwin Volcano is grouped with \\u003cem\\u003eP. andysabini\\u003c/em\\u003e from Wolf Volcano due to their genetic similarity \\u003cstrong\\u003eE.\\u003c/strong\\u003e Mantel test of the six \\u003cem\\u003ePhyllodactyllus\\u003c/em\\u003e species. The p-value was set to 0.05 (default).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5703179/v1/de3e646e0c95311382c3ee5b.png\"},{\"id\":96650174,\"identity\":\"3df5bc91-da9b-4384-81b1-f16250c0082a\",\"added_by\":\"auto\",\"created_at\":\"2025-11-24 16:09:13\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":2786653,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5703179/v1/e8bf1fbd-5a2e-4c1a-8c44-e68a13e653b5.pdf\"},{\"id\":75178492,\"identity\":\"db1d529e-9983-4db7-994a-002ea7a17ef5\",\"added_by\":\"auto\",\"created_at\":\"2025-01-31 15:42:25\",\"extension\":\"docx\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":431555,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementaryMaterials.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5703179/v1/ed068cd1a42e1f7ea2664bc9.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Genomic Insights and Biogeography of Endemic Galapagos Geckos: Unraveling Population Structure and Species Delimitation Across Human-Inhabited Islands\",\"fulltext\":[{\"header\":\"1. Introduction\",\"content\":\"\\u003cp\\u003eIslands offer invaluable opportunities for understanding evolutionary processes due to their isolation and distinct environmental conditions [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e]. Two important factors when studying evolutionary processes on islands are oceanic and topographic barriers. In volcanic islands, eruption events and landslides can produce habitat fragmentation and isolate populations, driving genetic differentiation and speciation within islands [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. Nonetheless, patterns of genetic differentiation between populations from different islands and populations within the same island suggest oceanic barriers are more effective than topographic barriers at promoting isolation in islands [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. The Galapagos Islands are renowned for their ecological significance and unique biodiversity. This volcanic archipelago located approximately 1,000 km off the coast of Ecuador serves as a natural laboratory for understanding mechanisms of adaptation and speciation [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe fauna of the Galapagos Islands includes several endemic gecko species. Geckos are one of the most diverse clades of lizards, with a worldwide distribution and a high diversity in the tropics. Many gecko clades have dispersed and diversified in island ecosystems due to their ability to traverse wide barriers [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e]. Geckos in island ecosystems have unique phenotypes due to the evolutionary processes product of their geographic isolation, which can profoundly impact their genetic structure, also influenced by intraspecific competition [\\u003cspan additionalcitationids=\\\"CR10\\\" citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e]. Understanding their genetic diversity within these island ecosystems is crucial for conserving their unique biodiversity [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe Galapagos Islands are home to eleven endemic species of leaf-toed geckos of the genus \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e (family Phyllodactylidae) [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. Additionally, four species of non-native geckos have arrived in the Galapagos over the last two centuries and established populations in human-inhabited islands (family Gekkonidae: \\u003cem\\u003eHemidactylus frenatus\\u003c/em\\u003e and \\u003cem\\u003eLepidodactylus lugubris\\u003c/em\\u003e; Phyllodactylidae: \\u003cem\\u003ePhyllodactylus reissii\\u003c/em\\u003e; and Sphaerodactylidae: \\u003cem\\u003eGonatodes caudiscutatus\\u003c/em\\u003e) [\\u003cspan additionalcitationids=\\\"CR15 CR16\\\" citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]. While large reptiles, such as giant tortoises, are among the best-studied inhabitants of the Galapagos [\\u003cspan additionalcitationids=\\\"CR19 CR20\\\" citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e], information about the evolutionary patterns, species diversity, biogeography, and ecological dynamics of smaller reptiles like the Galapagos leaf-toed geckos and Galapagos racer snakes remain unexplored, and the impacts caused by non-native species on their populations have yet to be understood [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eGalapagos leaf-toed geckos are primarily nocturnal, foraging on the ground, rocky crops, tree trunks, or buildings, and seeking shelter during the day under rocks, tree trunks, wood, lava blocks, and cactus stumps [\\u003cspan additionalcitationids=\\\"CR24 CR25\\\" citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. Six of the eleven endemic species of leaf-toed geckos occur on human-inhabited islands: \\u003cem\\u003ePhyllodactylus andysabini\\u003c/em\\u003e from Isabela Island, \\u003cem\\u003ePhyllodactylus baurii\\u003c/em\\u003e from Floreana Island, \\u003cem\\u003ePhyllodactylus leei and P. darwini\\u003c/em\\u003e from San Cristobal Island, \\u003cem\\u003ePhyllodactylus galapagensis\\u003c/em\\u003e from Santa Cruz Island, and \\u003cem\\u003ePhyllodactylus simpsoni\\u003c/em\\u003e from Isabela [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e is also found on Fernandina Island, which is an uninhabited island. \\u003cem\\u003ePhyllodactylus andysabini\\u003c/em\\u003e and \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e are allopatric in Isabela Island, with \\u003cem\\u003eP. andysabini\\u003c/em\\u003e restricted to the northern part of the island, while \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e occurs across central and southern regions. Only two of these species occur in sympatry, \\u003cem\\u003eP. leei\\u003c/em\\u003e and \\u003cem\\u003eP. darwini\\u003c/em\\u003e, both inhabiting San Cristobal Island. However, they are easily differentiated by their body size, with \\u003cem\\u003eP. darwini\\u003c/em\\u003e being the largest endemic gecko in the archipelago [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. These geckos face threats such as habitat change and loss, as well as impacts from introduced species that may act as predators, competitors, or carriers of diseases and parasites [\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e], similar to what has happened to endemic gecko populations on other tropical islands [\\u003cspan additionalcitationids=\\\"CR30 CR31 CR32 CR33 CR34 CR35\\\" citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eEndemic species hold significant ecological and evolutionary importance, due to their highly specialized adaptations to unique environments, making them key indicators of ecosystem health and resilience. Their restricted geographic ranges and high vulnerability to environmental changes underscore their critical role in conservation efforts to preserve biodiversity and maintain ecosystem balance [\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e]. Despite this, there are few genetic studies on \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e species native to Galapagos, and to our knowledge, no genomic studies have been reported to date. Existing genetic research on the Galapagos leaf-toed geckos has provided valuable insights into their evolutionary history and diversity, predominantly focusing on understanding the biogeographic patterns of the genus and its historical colonization dynamics within the archipelago [\\u003cspan additionalcitationids=\\\"CR39\\\" citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e]. Notably, studies from 2014 and 2016 by Torres-Carvajal et al. used nuclear and mitochondrial markers to shed light on the evolutionary history and diversification of the \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e genus from Galapagos and test colonization hypothesis [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e]. Another study used nuclear and mitochondrial markers to describe two new species from Isabela Island and presents an updated molecular phylogenic hypothesis of the genus \\u003cem\\u003ePhyllodactyus\\u003c/em\\u003e in the Galapagos [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e]. However, there is a need for more comprehensive genomic studies that can provide a deeper understanding of the mechanisms driving diversification and shaping the genetic diversity and population structure of Galapagos leaf-toed geckos.\\u003c/p\\u003e \\u003cp\\u003eThe aim of this study was to understand the genetic diversity and population structure of the six endemic Galapagos gecko species that are found on human-inhabited islands using RAD-Seq (Restriction Site Associated DNA Sequencing), which has proven to be a powerful method for understanding population dyanimcs and evolutionary processes in various organisms [\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e]. Our results reveal clearly defined species boundaries, with one notable exception, alongside robust population structure. Our results reveal well-defined species boundaries, with one notable exception, alongside a robust population structure apparently not influenced by anthropogenic factors, and low levels of genetic diversity. These findings offer valuable implications for informing conservation strategies, especially given the significant changes currently taking place in the Galapagos Islands as a result of human activities.\\u003c/p\\u003e\"},{\"header\":\"2. Results\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.1 RAD-seq\\u003c/h2\\u003e \\u003cp\\u003eA total of 95 DNA samples were processed for RAD-seq analysis in the present study. RAD-seq yielded a total of 1,021,167,325 forward reads and an equivalent number of reverse reads (Supplementary Table \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e). None of the sequences were flagged as poor quality. The sequence length for both files is uniform at 169 base pairs, which is consistent with the size selection performed for sequencing. The GC content differs slightly between the forward and reverse reads, with percentages of 49% and 48%, respectively. Notably, the mean sequence quality, as indicated by Phred scores, remains consistent across both the forward and reverse reads files, with a quality score of 36.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.2 Population Structure and Genetic Differentiation\\u003c/h2\\u003e \\u003cp\\u003eAfter processing through Stacks and VCFtools a final data set of 93 samples (two samples were eliminated, one due to low coverage and one due to high missing data, see methods) and 30,353 loci were used for population structure and genetic differentiation analyses. Figure\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eA illustrates the distribution of samples across Fernandina, Isabela, Santa Cruz, Floreana and San Cristobal islands. The principal component analysis (PCA) shows the differentiation between the 93 samples of \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e species studied. PC1(28%) \\u003cem\\u003evs.\\u003c/em\\u003e PC2 (23%) reveals three distinct clusters (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eB). \\u003cem\\u003eP. darwini\\u003c/em\\u003e comprises the first cluster, \\u003cem\\u003eP. leei\\u003c/em\\u003e forms the second cluster, while \\u003cem\\u003eP. baurii, P. galapagensis, P. simpsoni\\u003c/em\\u003e, and \\u003cem\\u003eP. andysabini\\u003c/em\\u003e are grouped in the third cluster. PC1(28%) \\u003cem\\u003evs.\\u003c/em\\u003e PC3 (14%) further separates the data distinguishing \\u003cem\\u003eP. baurii\\u003c/em\\u003e from \\u003cem\\u003eP. galapagensis, P. simpsoni\\u003c/em\\u003e, and \\u003cem\\u003eP. andysabini\\u003c/em\\u003e (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eC).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe unrooted phylogenetic tree (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA) elucidates the interrelationship among the sampled specimens, separating all \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e species, except for \\u003cem\\u003eP. andysabini\\u003c/em\\u003e, which is nested within the branch of \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e. Species are clustered according to their geographic location across the islands (Supplementary Table S2).\\u003c/p\\u003e \\u003cp\\u003eThe haplotype genealogy (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eB) grouped the six analyzed species into five distinct clusters. In accordance with the results from the phylogenetic tree, the five clusters correspond to different \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e species and \\u003cem\\u003eP. andysabini\\u003c/em\\u003e is found within the \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e cluster.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eF\\u003csub\\u003eST\\u003c/sub\\u003e estimates ranged from 0.524 to 0.981 (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eA). The lowest genetic divergence (F\\u003csub\\u003eST\\u003c/sub\\u003e = 0.524) was found between \\u003cem\\u003eP. galapagensis\\u003c/em\\u003e and the combined \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e/\\u003cem\\u003eP. andysabini\\u003c/em\\u003e group. \\u003cem\\u003eP. darwini\\u003c/em\\u003e presented high values of genetic divergence with the other species, being the highest with \\u003cem\\u003eP. baurii\\u003c/em\\u003e (F\\u003csub\\u003eST\\u003c/sub\\u003e = 0.961).\\u003c/p\\u003e \\u003cp\\u003eThe D\\u003csub\\u003eXY\\u003c/sub\\u003e analysis between the six \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e species generated values ranging from 0.02 to 0.117 (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eB). The most closely related species, \\u003cem\\u003eP. andysabini\\u003c/em\\u003e and \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e, showed the lowest value (D\\u003csub\\u003eXY\\u003c/sub\\u003e = 0.02), while the most genetically distinct species were \\u003cem\\u003eP. darwini\\u003c/em\\u003e and \\u003cem\\u003eP. baurii\\u003c/em\\u003e (D\\u003csub\\u003eXY\\u003c/sub\\u003e = 0.117).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eIn Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e, FST values were calculated among individuals from the different collection sites of a species on each island (see Supplementary Table S3 for details of sampling locations within each island). Specifically, Fig.\\u0026nbsp;4A1 and 4A2 corresponds to comparisons of \\u003cem\\u003eP. leii\\u003c/em\\u003e and \\u003cem\\u003eP. darwini\\u003c/em\\u003e sampling locations in San Cristobal, respectively. Figure\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eB depicts the genetic distances between \\u003cem\\u003eP. galapagensis\\u003c/em\\u003e sampling locations in Santa Cruz, Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eC shows \\u003cem\\u003eP. baurii\\u003c/em\\u003e genetic distances in Floreana, and Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eD represents the genetic distances within \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e and \\u003cem\\u003eP. andysabini\\u003c/em\\u003e sampling locations in Isabela and Fernandina Islands. The F\\u003csub\\u003eST\\u003c/sub\\u003e values follow a pattern corresponding to geographical distances, with the lowest values found in the closest collection sites, and the values increasing as the distances between sampling locations increase. For example, in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eC, P. \\u003cem\\u003ebaurii\\u003c/em\\u003e sampling locations exhibited a low F\\u003csub\\u003eST\\u003c/sub\\u003e value (0.04) between the west and north sampling locations (which are closer geographically) and a higher value (0.102) between the west and east sampling locations (which are farther apart). However, a Mantel test confirmed a significant correlation between geographic and genetic distances only for \\u003cem\\u003eP. galapagensis\\u003c/em\\u003e sampling locations on Santa Cruz Island (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eB and \\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eE, p-value\\u0026thinsp;=\\u0026thinsp;0.0001).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.3 Population Size and Genetic Diversity\\u003c/h2\\u003e \\u003cp\\u003e \\u003cem\\u003eP. baurii\\u003c/em\\u003e and \\u003cem\\u003eP. darwini\\u003c/em\\u003e exhibited the lowest values of expected heterozygosity (He), with 0.0175 and 0.0189, respectively, followed by \\u003cem\\u003eP. andysabin\\u003c/em\\u003ei with 0.0425. \\u003cem\\u003eP. leei\\u003c/em\\u003e and \\u003cem\\u003eP. galapagensis\\u003c/em\\u003e displayed higher values (0.0507 and 0.0595, respectively), and \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e had the highest He value (0.0794) (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Nucleotide diversity values displayed the same pattern: \\u003cem\\u003eP. darwini\\u003c/em\\u003e and \\u003cem\\u003eP. baurii\\u003c/em\\u003e showed the lowest values of nucleotide with values of 0.0023 and 0.0047, respectively, followed closely by \\u003cem\\u003eP. andysabini\\u003c/em\\u003e with a value of 0.0066. \\u003cem\\u003eP. leei\\u003c/em\\u003e and \\u003cem\\u003eP. galapagensis\\u003c/em\\u003e exhibited values of 0.0161 and 0.0168, respectively, and \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e showed the highest nucleotide diversity (0.0225).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eGenetic diversity parameters, expected heterozygosity (He) and nucleotide diversity (π), for the 93 \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e individuals studied.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"7\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"7\\\" nameend=\\\"c7\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eHeterozygosity (He) and Nucleotide diversity (π)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP. simpsoni\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP. baurii\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP. leei\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP. darwini\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP. galapagensis\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP. andysabini\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eHe\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.0794\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.0175\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.0507\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.0189\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.0595\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.0425\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eπ\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.0225\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.0047\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.0161\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.0023\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.0168\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.0066\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"3. Discussion\",\"content\":\"\\u003cp\\u003eOur study employed a comprehensive genomic approach, analyzing over 30,000 loci, and was able to elucidate the population structure and genetic differentiation among \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e species inhabiting human-populated islands in the Galapagos. This high-resolution analysis provided valuable insights into the genetic diversity within and between species, revealing distinct genetic clusters, challenging previous species classifications, and highlighting patterns of genetic diversity and differentiation.\\u003c/p\\u003e \\u003cp\\u003e \\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eGenetic clusters\\u003c/span\\u003e \\u003c/p\\u003e \\u003cp\\u003eAccording to the results obtained in the PCA (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e), the phylogenetic tree (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA) and the haplotype network (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eB), five distinct genetic clusters corresponding to \\u003cem\\u003eP. baurii\\u003c/em\\u003e, \\u003cem\\u003eP. galapagensis\\u003c/em\\u003e, \\u003cem\\u003eP. darwini\\u003c/em\\u003e, \\u003cem\\u003eP. leei\\u003c/em\\u003e, and a combined cluster for \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e and \\u003cem\\u003eP. andysabini\\u003c/em\\u003e were revealed. These findings confirm that \\u003cem\\u003eP. baurii, P. galapagensis\\u003c/em\\u003e, \\u003cem\\u003eP. darwini\\u003c/em\\u003e, and \\u003cem\\u003eP. leei\\u003c/em\\u003e are clearly defined species, as suggested by the literature [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e]. This is expected since most of these species are found on different islands, allowing them to evolve in isolation [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e]. Aside from \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e and \\u003cem\\u003eP. andysabini\\u003c/em\\u003e which will be discussed further on, \\u003cem\\u003eP. darwini\\u003c/em\\u003e and \\u003cem\\u003eP. leei\\u003c/em\\u003e are the only species in this study that occur in sympatry on the same island, however they are distinctly separated from each other e (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). This difference could be attributed to the more recent colonization of the island by the ancestor of \\u003cem\\u003eP. darwini\\u003c/em\\u003e, which is estimated to have occurred around 3\\u0026nbsp;million years ago. In contrast, evidence suggests that the ancestor of the other \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e species in the Galapagos colonized the islands 13\\u0026nbsp;million years ago, and since then these species have been isolated from their continental relatives [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e]. Additionally, the two species are phenotypically distinct, with \\u003cem\\u003eP. darwinii\\u003c/em\\u003e having a much larger body size compared to \\u003cem\\u003eP. leei\\u003c/em\\u003e, as well as a different scalation pattern and coloration [\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e]. The substantial size difference between these species, together with their disparate colonization times, likely facilitated the co-existence of these two distinct species on the same island by reducing competition for resources through niche partitioning [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe PCA (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e) shows the \\u003cem\\u003eP. galapagensis\\u003c/em\\u003e cluster in close proximity to the \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e - \\u003cem\\u003eP. andysabini\\u003c/em\\u003e combined cluster, while the phylogenetic tree and haplotype network (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e) separate these clusters into two clearly defined groups. These findings are consistent with the historical classification of \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e and \\u003cem\\u003eP. andysabini\\u003c/em\\u003e as part of \\u003cem\\u003eP. galapagensis\\u003c/em\\u003e, and their more recent phylogenetic divergence [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e]. Additionally, the \\u003cem\\u003eP. baurii\\u003c/em\\u003e cluster is closely related to the \\u003cem\\u003eP. galapagensis\\u003c/em\\u003e and \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e - \\u003cem\\u003eP. andysabini\\u003c/em\\u003e clusters, reflecting their phylogenetic relationships as reported by previous genetic studies [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e]. These results also reflect the chronological formation of the extant islands in the archipelago which are reported to have emerged in three distinct groups. San Crist\\u0026oacute;bal, where \\u003cem\\u003eP. leei\\u003c/em\\u003e occurs, arose around 2.5\\u0026nbsp;million years ago along with Espa\\u0026ntilde;ola. Santa Cruz (home to \\u003cem\\u003eP. galapaguensis\\u003c/em\\u003e), and Floreana (\\u003cem\\u003eP. bauri\\u003c/em\\u003e) formed between 1.5 and 2\\u0026nbsp;million years ago, along with the rest of the central islands. Finally, Isabela and Fernandina, where the \\u003cem\\u003eP. simpsoni\\u0026ndash;P. andysabini\\u003c/em\\u003e group is found, emerged about 0.5\\u0026nbsp;million years ago [\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003e \\u003cspan type=\\\"ItalicUnderline\\\" class=\\\"ItalicUnderline\\\" name=\\\"Emphasis\\\"\\u003eP, simpsoni\\u003c/span\\u003e \\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eand\\u003c/span\\u003e \\u003cspan type=\\\"ItalicUnderline\\\" class=\\\"ItalicUnderline\\\" name=\\\"Emphasis\\\"\\u003eP. andysabini\\u003c/span\\u003e \\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eas a single species\\u003c/span\\u003e\\u003c/p\\u003e \\u003cp\\u003eThe results of the D\\u003csub\\u003eXY\\u003c/sub\\u003e (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eB), PCA (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e), phylogenetic tree (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA) and haplotype network (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eB) collectively support the notion that \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e and \\u003cem\\u003eP. andysabini\\u003c/em\\u003e may not be separate species, contrary to the previous classification by Arteaga et al. (2019) who diagnosed them based on morphological traits and five genetic markers [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e]. Our study, utilizing over 30,000 loci, provides strong evidence that \\u003cem\\u003eP. andysabini\\u003c/em\\u003e and \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e are likely conspecific, which is supported by their shared habitat on Isabela Island and corroborated by previous genetic studies [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e]. It is noteworthy that the D\\u003csub\\u003eXY\\u003c/sub\\u003e value, which reflects the minimum nucleotide differences between the two species, is close to 0, which reinforces their genetic similarity and suggesting conspecificity [\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eArteaga et al. (2019) proposed two phenetic differences between \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e and \\u003cem\\u003eP. andysabini\\u003c/em\\u003e in their original description: the absence of supranasal contact and the presence of a densely stippled throat in \\u003cem\\u003eP. andysabini\\u003c/em\\u003e [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e]. However, individuals of \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e also were reported to exhibit these characteristics (43% individuals of \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e examined by Arteaga et al. (2019) had absence of contact between supranasals and 36% had a brown stippled throat) [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e]. Our data agree that these two characters are present in populations currently assigned to \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e. Therefeore, these morphological characters are not reliable discriminators. High-resolution RAD-Seq data support that all studied populations of Isabela and Fernandina Islands correspond to a single species. This technique has proven to be a powerful tool for detecting population structure and evolutionary patterns in species due to the use of a much larger number of loci than traditional markers, as well as the high depth of sequencing coverage it provides [\\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e]. Therefore, we propose the synonymy of \\u003cem\\u003ePhyllodactylus andysabini\\u003c/em\\u003e Arteaga, Bustamante, Vieira, Tapia, Carri\\u0026oacute;n \\u0026amp; Guayasamin, 2019 with \\u003cem\\u003ePhyllodactylus simpsoni\\u003c/em\\u003e Arteaga, Bustamante, Vieira, Tapia, Carri\\u0026oacute;n \\u0026amp; Guayasamin, 2019, making \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e the valid name for all gecko populations from Isabela and Fernandina islands.\\u003c/p\\u003e \\u003cp\\u003e \\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eGenetic differentiation between and within species\\u003c/span\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe F\\u003csub\\u003eST\\u003c/sub\\u003e and D\\u003csub\\u003eXY\\u003c/sub\\u003e values found in this study revealed a significant differentiation between species, with F\\u003csub\\u003eST\\u003c/sub\\u003e values ranging between 0.524 and 0.981 and D\\u003csub\\u003eXY\\u003c/sub\\u003e values between 0.02 and 0.117 (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). With the exception of \\u003cem\\u003eP. andysabini\\u003c/em\\u003e and \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e, these high values indicate clearly differentiated species [\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e]. Interestingly, the genetic differentiation between \\u003cem\\u003eP. darwini\\u003c/em\\u003e and all other species is higher than the values found between all other species (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). As mentioned previously, this could be due to the fact that \\u003cem\\u003eP. darwini\\u003c/em\\u003e is the result of a separate, more recent colonization event, and thus more genetically distinct from all the other species that derived from a single colonization event [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e]. Additionally, the genetic differentiation values seem to be consistent with the island formation age: species from older islands tend to have higher genetic differentiation values [\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eWhen analyzing the F\\u003csub\\u003eST\\u003c/sub\\u003e values within \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e, the highest value was found between the samples from the islands of Fernandina and Isabela. Despite this, the Mantel test did not yield significant results (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eD). It is very likely that the differentiation observed between individuals from these two islands is due to the body of water that separates them, since this acts as a barrier to gene flow, generating isolation and genetic differentiation between sampling locations from different islands [\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eF\\u003csub\\u003eST\\u003c/sub\\u003e values within \\u003cem\\u003eP. baurii\\u003c/em\\u003e, \\u003cem\\u003eP. leii\\u003c/em\\u003e and \\u003cem\\u003eP. darwini\\u003c/em\\u003e species were low, although a trend could be observed: individuals from opposite ends of each island were more genetically differentiated (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). However, the Mantel test was not significant, indicating no correlation between geographic distance and genetic divergence within these species. This could be due to the volcanic nature of these islands. Eruption events and landslides are phenomena that promote habitat fragmentation and genetic isolation, thereby driving speciation as well as differentiation within species living on the same island [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. Regarding \\u003cem\\u003eP. galapagensis\\u003c/em\\u003e, a clear difference was observed between northern and southern sampling locations, and the Mantel test indicated that this divergence can be attributed to geographic distances. This suggests that geographic distance could indeed play a role in shaping genetic differentiation within sampling locations of the same species [\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eAnthropogenic impacts are an important factor to consider when studying population differentiation and divergence in the islands. Human activity on islands like San Cristobal, Isabella and Santa Cruz has been substantial, including land use changes, tourism, and urbanization, which can fragment habitats and alter ecosystems [\\u003cspan citationid=\\\"CR56\\\" class=\\\"CitationRef\\\"\\u003e56\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e57\\u003c/span\\u003e] Despite this, notable genetic diversity and structure remain among gecko populations, suggesting resilience or isolated gene pools. Surprisingly, humans do not appear to be causing significant admixture among these populations; instead, population boundaries remain intact, suggesting that geographic or behavioral barriers are stronger than the influences of human activity in preventing gene flow. Conducting a detailed geographic analysis of sampling sites could provide further insights into how human activities and landscape features may be shaping or isolating gecko diversity, potentially indicating which populations are more vulnerable to future changes and highlighting conservation priorities [\\u003cspan citationid=\\\"CR56\\\" class=\\\"CitationRef\\\"\\u003e56\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003e \\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eGenetic diversity\\u003c/span\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe expected heterozygosity (He) values for \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e species endemic to the Galapagos Islands ranged from 0.0175 (\\u003cem\\u003eP. baurii\\u003c/em\\u003e) to 0.0794 (\\u003cem\\u003eP. simpsoni\\u003c/em\\u003e); while nucleotide diversity ranged from 0.0023 (\\u003cem\\u003eP. darwini\\u003c/em\\u003e) to 0.0225 (\\u003cem\\u003eP. simpsoni\\u003c/em\\u003e) (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Specific indicators of genetic diversity have not been calculated for other species within the \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e genus before this study, however research on gecko species has revealed varying levels of genetic diversity. For instance, in \\u003cem\\u003eGekko japonicus\\u003c/em\\u003e, Wei et al. (2015) found a mean expected heterozygosity of 0.395 to 0.797 in one population from Wenzhou, Zhejiang Province, China [\\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e], while Li et al. (2007) reported a range of 0.584 to 0.917 in different microsatellite markers in seven populations of \\u003cem\\u003eGekko swinhonis\\u003c/em\\u003e from China [\\u003cspan citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e58\\u003c/span\\u003e]. It is important to note that firstly, these species are not island species, therefore the genetic diversity values obtained may not be comparable to our study group. Secondly, these studies were done using microsatellite markers, which takes into account few loci (usually less than 20) compared to the thousands of loci analyzed using RAD-Seq.\\u0026nbsp;Microsatellites studies that chose only polimorphic loci can overestimate genetic diversity [\\u003cspan citationid=\\\"CR59\\\" class=\\\"CitationRef\\\"\\u003e59\\u003c/span\\u003e], and are not ideal for reflecting genome-wide genetic diversity [\\u003cspan citationid=\\\"CR60\\\" class=\\\"CitationRef\\\"\\u003e60\\u003c/span\\u003e]. In contrast, several studies have shown that techniques such as RAD-Seq are powerful tools for detecting genetic diversity [\\u003cspan citationid=\\\"CR61\\\" class=\\\"CitationRef\\\"\\u003e61\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR62\\\" class=\\\"CitationRef\\\"\\u003e62\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe relatively low genetic diversity found in the species of this study can be attributed to their endemic nature, as they are confined to a single island or, in the case of \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e, two islands. Endemic island species often exhibit lower genetic diversity due to various factors associated with their unique evolutionary history and the challenges posed by insular environments [\\u003cspan additionalcitationids=\\\"CR64 CR65\\\" citationid=\\\"CR63\\\" class=\\\"CitationRef\\\"\\u003e63\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR66\\\" class=\\\"CitationRef\\\"\\u003e66\\u003c/span\\u003e]. These species are characterized by reduced genetic variation, which can negatively impact their overall fitness and increase their susceptibility to extinction [\\u003cspan citationid=\\\"CR64\\\" class=\\\"CitationRef\\\"\\u003e64\\u003c/span\\u003e]. Recent population bottlenecks, rather than the lasting effects of island colonization alone, may have further contributed to the diminished genetic diversity[\\u003cspan citationid=\\\"CR63\\\" class=\\\"CitationRef\\\"\\u003e63\\u003c/span\\u003e]. Thus, the possible effect of these factors, including bottlenecks, limited gene flow and distinctive evolutionary trajectories of island species, have probably played an important role in the genetic makeup of these endemic species, leading to reduced genetic diversity.\\u003c/p\\u003e \\u003cp\\u003eWithin the studied species, \\u003cem\\u003eP. baurii\\u003c/em\\u003e and \\u003cem\\u003eP. darwini\\u003c/em\\u003e showed the lowest nucleotide diversity and expected heterozygosity values (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). In the case of \\u003cem\\u003eP. baurii\\u003c/em\\u003e, this presumably reflects the constraints imposed by its restricted geographic distribution [\\u003cspan citationid=\\\"CR67\\\" class=\\\"CitationRef\\\"\\u003e67\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR68\\\" class=\\\"CitationRef\\\"\\u003e68\\u003c/span\\u003e]. Floreana, the island where this gecko species is found, has a relatively small area of 173 km2. On the other hand, the low genetic diversity values observed in \\u003cem\\u003eP. darwini\\u003c/em\\u003e could be explained by its relatively recent colonization history, occurring only 3\\u0026nbsp;million years ago, which contrasts with the much older colonization events of other endemic \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e species in the archipelago, dating back 13\\u0026nbsp;million years [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e]. The lower genetic diversity we observed may reflect a more recent founder effect [\\u003cspan additionalcitationids=\\\"CR70\\\" citationid=\\\"CR69\\\" class=\\\"CitationRef\\\"\\u003e69\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR71\\\" class=\\\"CitationRef\\\"\\u003e71\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eIn all cases, the low nucleotide diversity and expected heterozygosity values (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e) may be further influenced by ongoing evolutionary pressures imposed by human activities [\\u003cspan citationid=\\\"CR72\\\" class=\\\"CitationRef\\\"\\u003e72\\u003c/span\\u003e]. These pressures include the presence of introduced predators like cats and rats, which exert predatory pressure on gecko species, as well as competition and predation from introduced gecko species in the archipelago that cohabit in some places with native species [\\u003cspan citationid=\\\"CR73\\\" class=\\\"CitationRef\\\"\\u003e73\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR74\\\" class=\\\"CitationRef\\\"\\u003e74\\u003c/span\\u003e]. Human habitat modifications might have also contributed to exacerbate the low genetic diversity observed in the species analyzed in this study [\\u003cspan additionalcitationids=\\\"CR76\\\" citationid=\\\"CR75\\\" class=\\\"CitationRef\\\"\\u003e75\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR77\\\" class=\\\"CitationRef\\\"\\u003e77\\u003c/span\\u003e].\\u003c/p\\u003e\"},{\"header\":\"4. Conclusion\",\"content\":\"\\u003cp\\u003eOur findings revealed clearly defined genetic clusters for five of our studied species: \\u003cem\\u003eP. darwini, P. baurii, P. simpsoni, P. galapagensis\\u003c/em\\u003e and \\u003cem\\u003eP. leei\\u003c/em\\u003e. We also observed population structure within species, likely influenced by land barriers such as volcanoes andan ocean barrier restricting gene flow. Our analyses led us to conclude that \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e and \\u003cem\\u003eP. andysabini\\u003c/em\\u003e exhibit very low genetic differentiation, leading us to propose their synonymization.\\u003c/p\\u003e \\u003cp\\u003eThe genetic relationships among species align with the chronological emergence of the Gal\\u0026aacute;pagos islands, suggesting that species diversification followed the island formation sequence. Additionally, while human activities such as land use changes, tourism, and urbanization have impacted islands like San Crist\\u0026oacute;bal, Isabela, and Santa Cruz, these activities appear to have limited influence on gene flow among gecko populations. The observed population boundaries seem to remain intact, likely due to strong geographic or behavioral barriers. A more detailed geographic analysis of sampling sites could further clarify how these factors contribute to genetic isolation and identify populations vulnerable to future environmental changes.\\u003c/p\\u003e \\u003cp\\u003eAs expected for endemic insular species mostly restricted to a single island, genetic diversity was found to be low across all studied species. \\u003cem\\u003eP. darwini\\u003c/em\\u003e displayed the highest genetic differentiation from other species, possibly due to its more recent colonization. This species, along with \\u003cem\\u003eP. baurii\\u003c/em\\u003e, exhibited the lowest genetic diversity. The reduced diversity in \\u003cem\\u003eP. baurii\\u003c/em\\u003e is likely attributable to its small geographic distribution, while the low diversity in \\u003cem\\u003eP. darwini\\u003c/em\\u003e may be a result of a more recent founder effect.\\u003c/p\\u003e \\u003cp\\u003eOur research findings highlight the importance of using high-resolution genomic tools to study genetic variation and population structure in islands. The knowledge gained from this research will not only enhance our understanding of the evolutionary processes shaping these species but also inform conservation strategies aimed at preserving their genetic integrity and ensuring their long-term survival in the face of anthropogenic challenges.\\u003c/p\\u003e\"},{\"header\":\"5. Methods\",\"content\":\"\\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e5.1 Sampling\\u003c/h2\\u003e \\u003cp\\u003eFieldwork was conducted in the Galapagos Archipelago from May to August 2023, in the islands of Santa Cruz, Isabela, Floreana, San Crist\\u0026oacute;bal, and Fernandina (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). We collected samples in 27 localities, encompassing urban and natural environments (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). We surveyed native gecko species of \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e during the day and night, searching in trees, dry logs, under rocks, under tree bark, and other natural and human-made potential refuges. At each site, we captured up to 10 adult individuals of each species present.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eLocations of sampled geckos\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSpecies\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eIsland\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eGeographic location\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eEcosystems\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003ePhyllodactylus andisabini\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eIsabela\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eNorthwest\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eLava\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003ePhyllodactylus baurii\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eFloreana\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eNorth, West, and East\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eDeciduous forest, urban area\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003ePhyllodactylus darwinii\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eSan Cristobal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eWest and East\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eSeasonal evergreen forest, deciduous forest, urban area\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003ePhyllodactylus galapagensis\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eSanta Cruz\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eNorth, East, and South\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eDeciduous forest, urban area\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003ePhyllodactylus leei\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eSan Cristobal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eNorth and South\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eDeciduous forest\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003ePhyllodactulus simpsoni\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eFernandina\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eNortheast\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eLava\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eIsabela\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eWest, East, and South\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eDeciduous forest, lava, urban area\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003e* Classification of ecosystems follows the proposal by Rivas-Torres et al. (2018)\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eWe collected 184 tail-tip tissue samples from endemic \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e individuals for genetic analyses (Supplementary Table S3).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e\\u003cb\\u003e5.2 DNA Extraction and RAD-Sequencing\\u003c/b\\u003e\\u003c/h2\\u003e \\u003cp\\u003eGenomic DNA was extracted from animal tails using a commercial DNeasy Blood \\u0026amp; Tissue kit (Qiagen) following manufacturer's instructions with modifications: we repeated each wash steps with buffers AW1 and AW2, and DNA was eluted in a final volume of 34 ul.\\u003c/p\\u003e \\u003cp\\u003eDNA concentration was measured using Qubit 3 (Thermo Fisher Scientific, USA), and DNA quality was assessed using a Nanodrop 2000 Spectrophotometer (Thermo Fisher Scientific, USA). DNA integrity was analyzed on a 1.5% agarose gel. Samples were normalized to meet Floragenex (Eugene, OR, USA) requirements.\\u003c/p\\u003e \\u003cp\\u003eThe DNA concentration and quality for each of the samples that were sent to Floragenex is shown in Supplementary Table S4. The values of DNA concentration among all samples ranged from 8,92 to 25,8 ng/ul. Few samples showed quality ratios outside of the expected range (1,8\\u0026thinsp;\\u0026minus;\\u0026thinsp;2,0). Supplementary Figure \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e illustrates the integrity of DNA samples through agarose gel electrophoresis, where distinct bands indicate the presence of high-quality, non-degraded DNA molecules, suitable for library preparation and sequencing.\\u003c/p\\u003e \\u003cp\\u003e95 samples were selected for sequencing, considering the quantity and quality of DNA and the representativeness of the sample distribution in and between islands (Supplementary Table S4).\\u003c/p\\u003e \\u003cp\\u003eRAD-Seq was conducted by Floragenex (Eugene, OR, USA) following standard protocols. Genomic DNA underwent quality assessment and quality control (QA/QC) measures before library preparation. The RAD libraries were constructed using the SbfI restriction enzyme. Following restriction, fragments of 169 base pairs were selected for sequencing.\\u003c/p\\u003e \\u003cp\\u003eSequencing of the RAD-Seq libraries was carried out using the Illumina NovaSeq6000 platform. The sequencing runs were performed with paired-end reads of 150 base pairs, employing the NovaSeq6000 S Prime 300 cycle kit (Sp300). Both lanes of the Sp300 flow cell were allocated exclusively for sequencing. The sequencing data were provided in fastq format for downstream analysis.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e5.3 Read processing and creation of loci catalogue using Stacks\\u003c/h2\\u003e \\u003cp\\u003eForward and reverse sequencing reads were analyzed using FastQC [\\u003cspan citationid=\\\"CR78\\\" class=\\\"CitationRef\\\"\\u003e78\\u003c/span\\u003e]. We then used Stacks v2.65 to filter reads and create a loci catalogue for our population structure and genetic diversity analyses. Specifically, we began using process_radtags to demultiplex and clean the reads, specifying barcode-dist-1 of 3 to allow three mismatches when rescuing single-end barcodes, -c/--clean to remove reads with uncalled bases, -q/--quality to discard low-quality reads, and -r/--rescue to rescue barcodes and cut sites. This approach retained over 80% of the reads.\\u003c/p\\u003e \\u003cp\\u003eAfter demultiplexing we ran the main Stacks pipeline consisting of ustacks (builds loci), cstacks (creates a catalog of loci), sstacks (matches samples against the catalog), gstacks (assembles paired-end contigs, calls variant sites, and genotypes samples), and populations (filters data, calculates population genetics statistics, and exports various data formats) [\\u003cspan citationid=\\\"CR79\\\" class=\\\"CitationRef\\\"\\u003e79\\u003c/span\\u003e]. Following the recommendations of Catchen et al. (2013) [\\u003cspan citationid=\\\"CR79\\\" class=\\\"CitationRef\\\"\\u003e79\\u003c/span\\u003e], Paris et al. (2017) [\\u003cspan citationid=\\\"CR80\\\" class=\\\"CitationRef\\\"\\u003e80\\u003c/span\\u003e] and Rivera-Col\\u0026oacute;n \\u0026amp; Catchen (2022) [\\u003cspan citationid=\\\"CR81\\\" class=\\\"CitationRef\\\"\\u003e81\\u003c/span\\u003e], and based on the scripts found in Cerca et al. (2021a) [\\u003cspan citationid=\\\"CR82\\\" class=\\\"CitationRef\\\"\\u003e82\\u003c/span\\u003e], we ran the aforementioned Stacks pipeline using the wrapper program denovo_map.pl, since no reference genome is available for \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e species. The populations were delineated according to our population map (list of our 95 \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e samples). We optimized the parameters -M (maximum nucleotide mismatches allowed between stacks to be merged into a locus) and -n (maximum nucleotide mismatches allowed between stacks during the construction of the catalog) within the ustacks and cstacks modules of the Stacks pipeline [\\u003cspan citationid=\\\"CR79\\\" class=\\\"CitationRef\\\"\\u003e79\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR80\\\" class=\\\"CitationRef\\\"\\u003e80\\u003c/span\\u003e], by exploring a range of values from 1 to 7 for both parameters. Subsequently, we analyzed the cumulative count of loci resulting from various combinations of -M and -n values to identify the inflection point at which the change in the count of -R80 loci (number of polymorphic loci present in at least 80% of the samples) approached zero. The combination of -M 3, -n 3, and -R 80 was determined as the optimal parameter set for the \\u003cem\\u003ede novo\\u003c/em\\u003e assembly of loci within the \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e sp. dataset.\\u003c/p\\u003e \\u003cp\\u003eWe followed the methodology outlined by Cerca et al. (2021b) to exclude samples and loci exhibiting a high degree of missing data[\\u003cspan citationid=\\\"CR83\\\" class=\\\"CitationRef\\\"\\u003e83\\u003c/span\\u003e]. Samples displaying a mean depth of coverage less than 35 x (individuals 3961 \\u003cem\\u003eP. galapagensis\\u003c/em\\u003e and 4140 \\u003cem\\u003eP. darwini\\u003c/em\\u003e)) were removed utilizing VCFtools v.0.1.5 with the --mean_depth flags [\\u003cspan citationid=\\\"CR84\\\" class=\\\"CitationRef\\\"\\u003e84\\u003c/span\\u003e]. Additionally, we used VCFtools to further filter dataset, by applying the following filters: a mean coverage depth between 15 and 200 (--min-meanDP 15 --max-meanDP 200) [\\u003cspan citationid=\\\"CR84\\\" class=\\\"CitationRef\\\"\\u003e84\\u003c/span\\u003e]. Finally, 93 out of 95 samples and 30,353 loci were retained for subsequent genetic diversity and phylogenetic analyses.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e5.4 Population structure analyses\\u003c/h2\\u003e \\u003cp\\u003ePrincipal component analysis (PCA) was conducted to assess the genetic variation between the 93 samples of \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e species using the R package \\u003cem\\u003eadegenet\\u003c/em\\u003e [\\u003cspan citationid=\\\"CR85\\\" class=\\\"CitationRef\\\"\\u003e85\\u003c/span\\u003e] following the PCA script of Cerca et al. (2021a) [\\u003cspan citationid=\\\"CR82\\\" class=\\\"CitationRef\\\"\\u003e82\\u003c/span\\u003e]. Before running the PCA we used the option \\u0026lsquo;--write-random-snp\\u0026rsquo; in the populations program to diminish linkage disequilibrium in the dataset. Using the program vcf2phylip.py with the \\u0026ndash;nexus flag [\\u003cspan citationid=\\\"CR86\\\" class=\\\"CitationRef\\\"\\u003e86\\u003c/span\\u003e], we derived a PHYLIP file from the dataset comprising all available sites. Then, we employed IQ-TREE v1.6.12 [\\u003cspan additionalcitationids=\\\"CR88\\\" citationid=\\\"CR87\\\" class=\\\"CitationRef\\\"\\u003e87\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR89\\\" class=\\\"CitationRef\\\"\\u003e89\\u003c/span\\u003e] to infer the phylogenetic relationships among the 93 individuals. The analysis uses the General Time Reversible (GTR) model, incorporating an ascertainment bias (ASC) correction option (-m GTR\\u0026thinsp;+\\u0026thinsp;ASC), and included 1,000 bootstrap replicates to determine bootstrap support (BS) values [\\u003cspan citationid=\\\"CR88\\\" class=\\\"CitationRef\\\"\\u003e88\\u003c/span\\u003e]. The resultant phylogenetic tree was generated with the Newick tree format code outputted by IQ-TREE and employing the \\u003cem\\u003eape\\u003c/em\\u003e package in R for visualization [\\u003cspan citationid=\\\"CR90\\\" class=\\\"CitationRef\\\"\\u003e90\\u003c/span\\u003e]. Finally, we constructed a haplotype genealogy graph using the Fitchi algorithm [\\u003cspan citationid=\\\"CR91\\\" class=\\\"CitationRef\\\"\\u003e91\\u003c/span\\u003e] with the parameters \\u003cem\\u003e-m 0.3\\u003c/em\\u003e and \\u003cem\\u003e-p auto\\u003c/em\\u003e, aiming to elucidate the transitions and transversions between the sampled sequences.\\u003c/p\\u003e \\u003cp\\u003eWe evaluated the extent of genetic differentiation among \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e species by computing Weir and Cockerham\\u0026rsquo;s F\\u003csub\\u003eST\\u003c/sub\\u003e [\\u003cspan citationid=\\\"CR92\\\" class=\\\"CitationRef\\\"\\u003e92\\u003c/span\\u003e] using VCFtools [\\u003cspan citationid=\\\"CR84\\\" class=\\\"CitationRef\\\"\\u003e84\\u003c/span\\u003e]. Here, \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e is grouped with \\u003cem\\u003eP. andysabini\\u003c/em\\u003e due to their genetic similarity and to ensure a minimum of five samples for F\\u003csub\\u003eST\\u003c/sub\\u003e comparisons (as five individuals per group is the minimum number normally used for pairwise F\\u003csub\\u003eST\\u003c/sub\\u003e calculations). Interspecies differentiation D\\u003csub\\u003eXY\\u003c/sub\\u003e analyses were performed to offer supplementary evidence of genetic divergence, employing the Fitchi algorithm [\\u003cspan citationid=\\\"CR91\\\" class=\\\"CitationRef\\\"\\u003e91\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eTo understand the genetic differentiation between sampling locations within species, we performed F\\u003csub\\u003eST\\u003c/sub\\u003e analysis using VCFtools using Weir and Cockerham\\u0026rsquo;s F\\u003csub\\u003eST\\u003c/sub\\u003e [\\u003cspan citationid=\\\"CR84\\\" class=\\\"CitationRef\\\"\\u003e84\\u003c/span\\u003e]. For \\u003cem\\u003eP. galapagensis\\u003c/em\\u003e and \\u003cem\\u003eP. baurii\\u003c/em\\u003e, we calculated pairwise F\\u003csub\\u003eST\\u003c/sub\\u003e for each sampling location, as there were at least five individuals per location. For the other species, PCAs were conducted for each species. If there were discernible clusters (i.e. the individuals formed clear, delimited groups in the PCA), the individuals were grouped according to the clusters for F\\u003csub\\u003eST\\u003c/sub\\u003e calculations. When there were no discernible clusters, individuals were grouped according to their geographic regions (i.e. North, South, East, West or Center of the island) (see Supplementary Table S3).\\u003c/p\\u003e \\u003cp\\u003eA Mantel test was conducted to assess spatial correlation among the species, utilizing the \\u003cem\\u003eadegenet\\u003c/em\\u003e package in R [\\u003cspan citationid=\\\"CR85\\\" class=\\\"CitationRef\\\"\\u003e85\\u003c/span\\u003e]. The first matrix used for the Mantel test consisted of the F\\u003csub\\u003eST\\u003c/sub\\u003e matrix within each species. For the second matrix, we employed one geographic coordinate per location (for grouped \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e individuals) (see Supplementary Table S3).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e5.5 Calculation of genetic diversity\\u003c/h2\\u003e \\u003cp\\u003eTo understand the genetic diversity among species, we computed the expected heterozygosity (He) using the populations software in Stacks 2.65 [\\u003cspan citationid=\\\"CR79\\\" class=\\\"CitationRef\\\"\\u003e79\\u003c/span\\u003e]. Additionally, we calculated nucleotide diversity (π) using the Fitchi algorithm [\\u003cspan citationid=\\\"CR91\\\" class=\\\"CitationRef\\\"\\u003e91\\u003c/span\\u003e].\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e \\u003ch2\\u003eCompeting interests\\u003c/h2\\u003e \\u003cp\\u003eThe authors declare no competing interests.\\u003c/p\\u003e \\u003c/p\\u003e\\u003ch2\\u003eFunding\\u003c/h2\\u003e \\u003cp\\u003eThis research was funded by Gal\\u0026aacute;pagos Conservancy under the grant number \\u003cem\\u003eGal\\u0026aacute;pagos Conservancy USFQ 1\\u003c/em\\u003e, as part of a partnership between Gal\\u0026aacute;pagos Conservancy and Universidad San Francisco de Quito (USFQ).\\u003c/p\\u003e\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eM.L.T.: conceptualization, supervision, methodology, writing\\u0026mdash;review and editing. G.P.: methodology, investigation, formal analysis, writing\\u0026mdash;original draft, writing\\u0026mdash;review and editing. D.C.-H.: conceptualization, funding acquisition, writing\\u0026mdash;review and editing. J.J.G., M.J.P.: investigation, writing\\u0026mdash;original draft, writing\\u0026mdash;review and editing. J.C.: formal analysis, writing\\u0026mdash;review and editing. P.A.-B., M.V.S: formal analysis, writing\\u0026mdash;original draft. M.D.-J.: sample collection, writing\\u0026mdash;original draft, writing\\u0026mdash;review and editing. E.P.-R., D.B.-Z., D.V.: writing\\u0026mdash;original draft.\\u003c/p\\u003e\\u003ch2\\u003eAcknowledgement\\u003c/h2\\u003e\\u003cp\\u003eThe authors would like to thank Ver\\u0026oacute;nica Baquero, Pamela Borja and Daniel D\\u0026aacute;vila for their contributions to the DNA extractions in this project. We thank the Gal\\u0026aacute;pagos National Park Directorate, including Galo Quezada, Daniel Lara, Jorge Carri\\u0026oacute;n, Carlos Vera, and all authorities and park rangers of the Galapagos National Park for their valuable comments during project proposal reviews and support with logistics and transportation to the sampling sites. Special thanks to Carlos Mena, Sof\\u0026iacute;a Tacle, Leandro Vaca, Cecibel Narv\\u0026aacute;ez, Anita Carri\\u0026oacute;n, Sylvia and Jessenia Sotamba, Juan Pablo Mu\\u0026ntilde;oz, Marjorie Riofr\\u0026iacute;o, Daniela Alarc\\u0026oacute;n, Paola Carri\\u0026oacute;n, Cristina Vintimilla, M\\u0026aacute;ximo, and Marlene Ochoa, and all the personnel from the Galapagos Science Center GSC (Universidad San Francisco de Quito USFQ and University of North Carolina at Chapel-Hill UNC) and Universidad San Francisco de Quito, GAIAS Galapagos extension for their constant support and help. We acknowledge the GSC for providing access to equipment, labs, and other facilities. This research was conducted under a research permit (PC-32-22) issued by the Galapagos National Park Directorate and a framework contract on access to genetic resources (MAATE-DBI-CM-2022-0240) issued by the Ministry of Environment, Water and Ecological Transition of Ecuador.\\u003c/p\\u003e\\u003ch2\\u003eData Availability\\u003c/h2\\u003e\\u003cp\\u003eThe RADSeq data generated in this study are available from the NCBI Sequence Read Archive (SRA) under accession number PRJNA1200672. This includes raw sequence reads for 95 individuals across six endemic Phyllodactylus gecko species.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eWollenberg Valero, K. C. et al. Patterns, Mechanisms and Genetics of Speciation in Reptiles and Amphibians. \\u003cem\\u003eGenes\\u003c/em\\u003e \\u003cb\\u003e10\\u003c/b\\u003e, 646 (2019).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCerca, J. et al. Evolutionary genomics of oceanic island radiations. \\u003cem\\u003eTrends Ecol. Evol.\\u003c/em\\u003e \\u003cb\\u003e38\\u003c/b\\u003e, 631\\u0026ndash;642 (2023).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMairal, M. et al. Paleo-islands as refugia and sources of genetic diversity within volcanic archipelagos: The case of the widespread endemic \\u003cem\\u003eCanarina canariensis\\u003c/em\\u003e (Campanulaceae). \\u003cem\\u003eMol. 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Fitchi: haplotype genealogy graphs based on the Fitch algorithm. \\u003cem\\u003eBioinformatics\\u003c/em\\u003e \\u003cb\\u003e8\\u003c/b\\u003e, 1250\\u0026ndash;1252 (2016).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWeir, B. S. \\u0026amp; Cockerham, C. C. Estimating F-statistics for the analysis of population structure. \\u003cem\\u003eEvolution\\u003c/em\\u003e \\u003cb\\u003e38\\u003c/b\\u003e, 1358\\u0026ndash;1370 (1984).\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"scientific-reports\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"scirep\",\"sideBox\":\"Learn more about [Scientific Reports](http://www.nature.com/srep/)\",\"snPcode\":\"\",\"submissionUrl\":\"\",\"title\":\"Scientific Reports\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Scientific Reports\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Galapagos Islands, geckos, Phyllodactylus, Genetic diversity, Population structure, RAD-seq\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-5703179/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-5703179/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eIslands offer invaluable opportunities for studying evolutionary processes due to their isolation and distinct environmental conditions. The Galapagos Islands, renowned for their rich biodiversity, host several endemic gecko species of the genus \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e (Gekkota: Phyllodactylidae). Despite their importance derived from their specialized adaptations and their crucial role in maintaining ecosystem balance, few studies have been conducted on these geckos. This highlights the need for comprehensive genomic research to understand their evolutionary patterns and population dynamics. This study elucidates the genetic diversity and population structure of six endemic \\u003cem\\u003ePhyllodactylus\\u003c/em\\u003e species found on four human-inhabited islands in the Galapagos using a RAD-Seq approach. The analysis of over 30,000 loci from 93 individuals revealed five distinct genetic clusters, corresponding to \\u003cem\\u003eP. baurii, P. galapagensis, P. darwini, P. leei\\u003c/em\\u003e, and a combined cluster of \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e and \\u003cem\\u003eP. andysabini\\u003c/em\\u003e. Our results indicate that \\u003cem\\u003eP. galapagensis\\u003c/em\\u003e clusters with the \\u003cem\\u003ecombined P. simpsoni - P. andysabini\\u003c/em\\u003e group, while \\u003cem\\u003eP. baurii\\u003c/em\\u003e shows close genetic relationships with both clusters, in accordance with the obtained phylogeny and the sequential emergence of the Galapagos Islands where each species is found. Substantial genetic differentiation was observed between species, with high F\\u003csub\\u003eST\\u003c/sub\\u003e and D\\u003csub\\u003eXY\\u003c/sub\\u003e values. However, our analyses indicate that gecko populations from across Isabela and Fernandina islands exhibit very low genetic differentiation, leading us to propose the synonymization of \\u003cem\\u003eP. andysabini\\u003c/em\\u003e with \\u003cem\\u003eP. simpsoni\\u003c/em\\u003e. Within-species population structure was associated with geographic barriers and gene flow restrictions. Surprisingly, human activity does not appear to be causing significant admixture among these populations; instead, population boundaries remain intact, indicating that geographic or behavioral barriers are stronger than human influences in limiting gene flow. Overall, we found low genetic diversity across species, probably due to their endemic nature and island isolation. This genomic study provides insights into the evolutionary dynamics shaping these unique geckos and highlights the importance of employing high-resolution genomic tools in insular ecosystems for their effective conservation and management.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Genomic Insights and Biogeography of Endemic Galapagos Geckos: Unraveling Population Structure and Species Delimitation Across Human-Inhabited Islands\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-01-31 15:42:19\",\"doi\":\"10.21203/rs.3.rs-5703179/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":2}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"scientific-reports\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"scirep\",\"sideBox\":\"Learn more about [Scientific Reports](http://www.nature.com/srep/)\",\"snPcode\":\"\",\"submissionUrl\":\"\",\"title\":\"Scientific Reports\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Scientific Reports\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"486054f0-9575-4cfd-842e-baa1061bf998\",\"owner\":[],\"postedDate\":\"January 31st, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[{\"id\":43258444,\"name\":\"Biological sciences/Ecology/Biogeography\"},{\"id\":43258445,\"name\":\"Biological sciences/Genetics/Population genetics\"},{\"id\":43258446,\"name\":\"Biological sciences/Genetics/Population genetics/Genetic variation\"}],\"tags\":[],\"updatedAt\":\"2025-11-24T16:02:52+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-5703179\",\"link\":\"https://doi.org/10.1038/s41598-025-24790-2\",\"journal\":{\"identity\":\"scientific-reports\",\"isVorOnly\":false,\"title\":\"Scientific Reports\"},\"publishedOn\":\"2025-11-20 15:58:18\",\"publishedOnDateReadable\":\"November 20th, 2025\"},\"versionCreatedAt\":\"2025-01-31 15:42:19\",\"video\":\"\",\"vorDoi\":\"10.1038/s41598-025-24790-2\",\"vorDoiUrl\":\"https://doi.org/10.1038/s41598-025-24790-2\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-5703179\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-5703179\",\"identity\":\"rs-5703179\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}