The ecological niche and population history shape mosquito population genetics: a case study from Caribbean islands

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Trimbos, Marieta A.H. Braks, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5250794/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 May, 2025 Read the published version in Parasites & Vectors → Version 1 posted 10 You are reading this latest preprint version Abstract Background: Despite their medical and veterinary importance, little is known about the general patterns in genetic population structure of mosquitoes. The scarce information that is available comes from a small subsample of cosmopolitan (and often pathogen-transmitting) species. This greatly hampers our ability to generalise previously described patterns of variation in mosquito population genetics to global mosquito biodiversity. This study aimed to explore variation in population genetics of species from a wide range of ecological niches and how variation in these patterns relates to species-specific ecologies and population history, using the mosquito fauna of the Caribbean islands of Aruba, Curaçao, and Bonaire as a case study. Methods: Mitochondrial COII sequences were obtained from 258 mosquito specimens belonging to six species, occurring on all three islands. Sequences were used in phylogenetic analysis and haplotype network analysis to assess the genetic variation between mosquito populations of each of the six ecologically diverse species, which vary in both their population history and ecological niche. Results: Both the genetic diversity and population genetic structure were found to differ strongly between sets of species, leading to a subdivision into three species groups: i) non-native species with low genetic diversity across all three investigated islands; ii) locally native species with high genetic diversity and closely related haplotypes occurring on different islands; iii) locally native species with high genetic diversity and locally restricted haplotypes. Conclusions: Our results show that the population genetics of non-native and native species strongly differ, likely as a result of population history. Furthermore, the results suggest that native populations may display distinct population genetic structure, which is likely related to differences in their ecology and dispersal capacity. Based on these results, we hypothesize that similar contrasts in mosquito population genetics along historical and ecological axes may be present worldwide. Mosquitoes Genetic diversity Population structure Haplotype network Dispersal Mitochondrial DNA Introduced species Dutch Caribbean. Figures Figure 1 Figure 2 Figure 3 Background Globally, there are approximately 3,700 species of mosquitoes (Diptera: Culicidae) [ 1 ]. Although much is known about the ecology and distribution of a limited number of species, most notably the species of medical importance (e.g., [ 2 – 6 ]), the majority of species is greatly understudied. Similarly, mosquito population dynamics and structure have been studied using population genetics almost exclusively in relation to pathogen transmission and vector control (e.g., [ 7 – 10 ]). As a result, the scarce information on mosquito population genetics that is currently available, is mostly based on a small subset of mosquito biodiversity, representing only a small fraction of the ecological diversity among mosquitoes. These well-studied, medically relevant species are often introduced outside of their native range and therefore globally widespread (e.g., [ 11 – 15 ]), which likely coincides with a particular pattern in population genetic structure [ 16 ]. Hence, it remains unclear how population genetics of mosquitoes vary among native species with different ecological strategies, and whether these patterns differ from introduced well-studied species. Emerging evidence demonstrates that commonly introduced species, such as Culex quinquefasciatus Say, 1823 and Aedes aegypti (Linnaeus, 1762), exhibit noticeable differences in both ecology as well as population genetic structure compared to native species. Recent studies often find a reduction in genetic diversity among introduced mosquito populations outside their native range compared to their source populations, which often display a much higher degree of genetic diversity (e.g., [ 16 – 23 ]). In contrast, among the few studies on locally native species there are notable observations of local radiation and speciation (e.g., in the Anopheles punctulatus group on the Solomon Islands [ 24 ], in the Ae. taeniorhynchus (Wiedemann, 1821) population on the Galápagos Islands [ 25 ], and in Cx. fuscanus Wiedemann, 1820 populations in India, [ 26 ]). These observations of local radiation indicate a potential contrast between the well-studied non-native and the understudied local mosquito species, suggesting profoundly different patterns in population genetic structure among these groups. Studying the population genetics of a variety of mosquito species in a single area allows for direct comparison of the population genetic structure of different species in relation to their behaviour and ecology, since the species studied will have been subjected to similar macro-environmental conditions. Hence, to elucidate how natural variation in population genetics relates to mosquito species ecology, patterns in genetic structure need to be studied across a more diverse assemblage of mosquito species in a single area. For this purpose, islands of moderate size offer compelling model systems due to several advantages. Such islands provide the opportunity to sample populations across their entire local distribution, presenting a more complete and reliable representation of the overall population structure. Moreover, the surrounding ocean likely isolates the islands from most natural colonisation events by mosquitoes [ 27 , 28 ]. The Dutch Leeward Antilles, comprising Aruba, Curaçao, and Bonaire, provide an ideal study case to investigate the variation in mosquito population genetics, due to the presence of a patchy mosaic of various distinct habitat types on these islands (e.g., [ 29 ]) in combination with a rich local mosquito fauna consisting of both native and non-native species [ 30 ]. The objective of this study is to explore the variation in mosquito population genetics by comparing the genetic diversity and population genetic structure among a comprehensive assemblage of native and non-native mosquito species. By analysing both native and non-native mosquito species with a broad range of ecological niches, we aim to gain new insights on the role of species-specific ecology in mosquito population genetics. We hypothesise that, in a given area, population genetics of mosquitoes differ between native and non-native populations along both a historical and an ecological axis. More specifically, we expect 1) species with a stricter ecological niche to comprise more unique haplotypes, because their populations are more easily fragmented when suitable habitat has a patchy spatial distribution, and 2) that non-native species exhibit a much smaller genetic radiation, resulting from less time to accumulate new mutations. To achieve the objectives, we used mitochondrial COII (or COX2 , cytochrome c oxidase subunit 2) sequences to perform haplotype network analysis, supported by phylogenetic analysis, for six diverse species of mosquitoes in the southern Caribbean. Methods Study site Variation in genetic diversity and population genetic structure among ecologically diverse mosquito species was explored on the islands of Aruba, Curaçao, and Bonaire in November and early December 2022 (Fig. 1), during the ‘Expedition ABC Mug-Sangura 2022’. Aruba (180 km 2 ) and Bonaire (288 km 2 ) were sampled for six days, while Curaçao, a slightly larger island (444 km 2 ), was sampled for eight days. The mosquito samples used in the genetic analysis were obtained from the larger collections made during this expedition. Some additional samples from Bonaire were obtained from the ‘Naturalis Relay Expedition 2022-2023’, collected between 1-14 December 2022. The islands are located in the southern Caribbean Sea, approximately 30 to 80 km off the coast of Venezuela, and follow a west to east gradient, with Aruba and Curaçao approx. 80 km apart and Curaçao and Bonaire approx. 45 km apart (Fig. 1). All three islands have a semi-arid tropical savannah climate and offer a rich diversity of habitats, including dry tropical forests, streams, freshwater and saltwater lakes, mangroves, caves, rocky and sandy shores, as well as various urban habitats [29]. The fieldwork was carried out during the late rainy season, which typically lasts from October to December/January on the islands [31], with heavy rainfalls during the months preceding the fieldwork [32, 33], likely causing high densities of mosquitoes. Sampling strategy The mosquitoes included in this study were sampled using a variety of trapping methods to increase the chances of collecting both individuals with common and rare haplotypes among local populations. Adult mosquitoes were trapped using CO 2 -baited BG Pro traps (Biogents, Regensburg, Germany), which were set up in 31 locations (Fig. 1) during daytime and emptied the next morning. The traps were used as EVS-style traps by hanging them approximately 100 cm [34] above the ground in a sheltered place (e.g., within vegetation). CO 2 was generated through sugar fermentation, utilizing a mixture of beet sugar, active-dry yeast, yeast nutrient salt, and tap water. Additionally, 24 locations (Fig. 1) were sampled for adult mosquitoes through human landing catches or by catching flying and resting mosquitoes with a net and aspirator. Larval sampling was performed by primarily using 350 ml Mosquito Dippers (BioQuip Products, Rancho Dominguez, California); smaller water bodies were sampled with turkey basters, soup spoons, or manual hand suction pumps [35]. Larval samples were taken from a diverse range of water bodies (n=53), such as ponds, lakes, seashore water bodies, streams, rainwater puddles, rock pools, crab holes, bromeliads, tree holes and artificial containers. Mosquitoes were collected from different areas on the islands, both coastal and inland regions, aiming for a wide coverage of the entire islands (Fig. 1). Suitable terrestrial and aquatic sampling sites were identified on sight or selected based on arial maps and expertise of local collaborators. Upon collection, live specimens were put in the freezer for at least 20 minutes prior to morphological identification. Identification was done morphologically with an unpublished identification key for the islands, which was constructed based on existing literature and keys for the region ([30, 36 – 41]). After identification, specimens were stored in 70% ethanol and several undamaged adult specimens were mounted. Taxon selection & specimen selection To obtain reliable insights into the local variation in mosquito population structure and genetic diversity on the islands, species were selected according to the following three criteria: they i) were among the most abundant species on the islands, ii) occupied different ecological niches, and iii) constituted a mix of native and non-native mosquito species. Of the 16 species of mosquitoes recorded during the expedition (Additional file 1: Table S1), nine species were observed only on a single island, or in a limited number of locations, and were consequently excluded from further analysis. Based on the criteria, specimens of six species were included in this study, which represent a variety of ecological strategies: Ae. aegypti , Ae. taeniorhynchus , Cx. nigripalpus Theobald, 1901, Cx. quinquefasciatus , a currently undescribed species of Deinocerites , and Haemagogus chrysochlorus Arnell, 1973. The native species include two species breeding in dynamic and temporary water bodies ( Cx. nigripalpus , breeding in temporary freshwater bodies, and Ae. taeniorhynchus , breeding in coastal temporary water bodies), and two species with highly specialised breeding habitats ( Deinocerites sp., breeding in crab burrows in the mangrove, and Hg. chrysochlorus , breeding in tree holes) [30, 38, 42]. The non-native species Ae. aegypti and Cx. quinquefasciatus are opportunistic container breeders with a strong association to urban areas [30, 38]. Both are considered to have invaded and colonised the Caribbean in the 16 th century [43, 44]. The aim was to include between 30-60 specimens per species in total for genetic analysis. To ensure a geographical spread of data points on each island, specimens were randomly subsampled from eight sections per island. A polygons for each island was manually created, before being divided into eight equally large sections by performing K-means clustering in QGIS (version 3.28. 2 Firenze) on a random point layer (100.000 points) within the island polygon. By creating Voronoi polygons and taking the intersect with the island polygon, new polygons for eight equally large sections per island were created (Fig. 1). For each island section, a sample location was selected with the sample() function in a basic randomiser script in RStudio (version 2022.12.0 Build 353; R version 4.2.1). From every selected location, three specimens were taken, preferably adult samples as adult DNA extractions had significantly higher success rates than larval extractions during a DNA extraction pilot in the lab. If fewer than three specimens of a given species were collected at a selected location, additional specimens were randomly subsampled to obtain three specimens per species per island section, aiming for an even distribution of the number of specimens per island section. Ultimately, the total number of specimens differed per species or islands, because of locally low abundance of some species on specific islands, or technical difficulties during the extraction or sequencing phase (Table 2). The specimens are all vouchered and stored in the Culicidae collection of Naturalis Biodiversity Center, formerly the National Museum of Natural History, Leiden, the Netherlands (RNMH). DNA extraction and amplification To elucidate patterns in the population genetics of local mosquito populations, mitochondrial DNA (mtDNA) was used. Since the haploid mitogenome is exclusively inherited maternally [45], the effective population size is four times smaller than in nuclear DNA, resulting in faster lineage sorting [46 – 48]. Theoretically, this enables mtDNA to reflect changes in population structure on shorter time scales [49], increasing chances of detecting changes in population structure. Based on an unpublished dataset of mitochondrial genomes of Dutch mosquitoes, four genes were compared regarding their intraspecific variability. Compared to COI (used in [50, 51]), ND4 (used in [52]), and ND5 (used in [25]), the COII gene (used in [25]) showed the highest intraspecific genetic diversity. Extractions on adult specimens were carried out using a single leg, which was rinsed with ddH 2 O for 10 minutes and dried (adapted from [53]). DNA extraction was performed using 20 μl Lucigen QuickExtract DNA Extraction Solution (Lucigen, Middleton, Wisconsin), following the manufacturer’s protocol with the following adaptations: the first incubation at 65°C for 15 minutes, and the second incubation at 98°C for 2 minutes. For larval specimens, 1-2 segments cut from the abdomen were used, or the entire abdomen for tiny larvae. Larval DNA extraction had low success rates using Lucigen QuickExtract and was therefore performed using the Higher Purity Tissue DNA purification kit (Canvax Biotech, Valladolid, Spain), following the protocol of the manufacturer. DNA of Cx. quinquefasciatus larvae was extracted using a DNeasy Blood & Tissue kit (QIAGEN, Hilden, Germany) following the manufacturer’s protocol, with the adaptation of using 50 μl of provided Buffer AE for DNA elution. The Canvax and QIAGEN kits had similar DNA yields. Samples were stored at -20°C. Each PCR reaction was prepared with 2.0 μl of DNA extract, 17.5 μl of Hot Start Taq 2X Master Mix (New England Biolabs, Ipswich, Massachusetts), 1.4 μl (10 μM stock) of forward and reverse primer, and 12.7 μl of nuclease-free water, adding up to a volume of 35 μl per reaction. The three primer sets used varied for different species (Table 1), but all targeted the same 745 bp locus. One newly developed reverse primer was utilized during this study (Cul-COII-R, see Table 1). The forward primer annealing site was located in tRNA-Leu DNA, and the reverse primer annealing site was in tRNA-Lys, resulting in an amplicon that included the COII gene. The PCR protocol was the same for all three primer sets, except for the annealing temperature (see Table 1): 30 s of initial denaturation at 95°C, followed by 35 cycles of 30 s denaturation at 95°C, 30 s annealing, and 1 min extension at 68°C, concluded with 5 min final extension at 68°C. All PCR products were checked on 1%-agarose gels, before sending out for Sanger sequencing. The Sanger-sequencing data of Ae. taeniorhynchus specimens contained multiple conflicting base calls in specific positions in the forward and reverse sequences, potentially resulting from Nuclear Mitochondrial DNA segments (NUMTs, see [54] and [55]. To eliminate ambiguities, all samples of this species were sequenced again using Oxford Nanopore sequencing [56]. Nanopore sequences a single DNA fragment, allowing us to analyse the individual reads at locations that otherwise returned double peaks in the chromatogram derived from Sanger sequencing. During the first PCR, the ONT-CO2F/ONT-Ae-COII-R primers were used (F-primer: 5’-TTTCTGTTGGTGCTGATATTGCATGGCAGATTAGTGCAATGA-3’ and R-primer: 5’-ACTTGCCTGTCGCTCTATCTTCGATTTAAGAGATCATTACTTGC-3’), followed by a second PCR using the Oxford EXP-PBC096 Barcode kit and LongAmp Taq 2X master mix. Every PCR was followed by sample quality checks on E-Gel and tapestation and a bead-clean-up with MN-beads. After end-repair, another MN-bead clean-up, and ligation of the Sequencing Adapters with the Oxford SQK-LSK114 Ligation Sequencing Kit v14, the DNA was loaded onto a Flongle flow cell for sequencing using Oxford GridION. Sequence alignment and analysis Raw sequences were trimmed and aligned in Unipro Ugene software (version 45.1; [57]) to obtain full sequences of the COII marker gene (684 bp). Sequences with many ambiguities were excluded from the analysis. Finalised sequences were aligned using the MUSCLE default algorithm [58] and converted to Nexus-format text-files as described by Leigh et al. [59]. All finalised sequences are available in the “Caribbean Mosquitoes (CAMOZ)” project on BOLD [60] under accession numbers CAMOZ009-23 – CAMOZ363-24. Haplotype network analysis was performed using PopART software (version 1.7; [61]) to infer genealogical relationships among the studied specimens. Haplotype networks were plotted per species using the Median-Joining network (MJN) inference method [62]. The number of haplotypes ( H ) and the number of segregating sites ( S ) were also retrieved from PopART. Additionally, all species were plotted in a single haplotype network (Additional file 1: Fig. S1) using the TCS method [63], which reduced the formation of complex knots in between species in the network. In addition to haplotype network analysis, DnaSP software (version 6.12; [64]) was used to calculate the nucleotide diversity ( π ), haplotype diversity ( Hd ), Tajima’s D, and Fu’s F S per species. Tajima’s D estimates if mutations occur due to neutral evolution or selective pressures by taking the difference between observed and expected nucleotide diversity [65]. Fu’s F S statistic is a similar neutrality test like Tajima’s D , but uses the haplotype distribution [66]. Since these statistics are both influenced by changes in population size, it can be used to detect past population expansions. Negative values for both neutrality tests represent an excess frequency of rare polymorphisms or alleles, indicative of recent population expansion or genetic hitchhiking [67]. Two positions were masked for Ae. aegypti sequences in PopART and DnaSP, due to ambiguous base calls. To support the results from the haplotype network analysis, a phylogenetic analysis including all successful sequences was performed. IQ-Tree2 [68] was used to calculate a Maximum Likelihood tree, using standard model selection with ModelFinder [69] and 1000 Ultrafast bootstraps [70]. The TPM2u+F+G4 was selected as best-fit model according to the BIC value by ModelFinder. Intraspecific branching is depicted as a triangular radiation (henceforth referred to as ‘collapsed’ branching). A wider triangle represents longer internal branch lengths in the respective collapsed clade. Branch length represents genetic distance between specimens. Support values are given per node as bootstrap values (%). The calculated tree was visualised using packages ggtree (version 3.10.0; [71]) and phytools (version 2.0-3; [72]) in R (version 2023.12.0 Build 369; R version 4.3.2). Results Mosquito collection In total, COII sequences of 258 mosquitoes belonging to six species were successfully obtained during this study (Table 2). Sequences were obtained from mosquitoes collected from a total of 108 different sampling locations (all species combined), with a wide geographical coverage of each island, and each species was collected on all three islands (Fig. 1 and Additional file 1: Fig. S2-3). Roughly equal numbers of specimens were used from each island for all species except Hg. chrysochlorus , which was found only in a single location in Aruba. Phylogenetic relationships All clades at species level were resolved as monophyletic, confirming that the included species are indeed genetically well separated populations with likely no gene flow between the species studied (Fig. 2). All clades had strong support values (≥90 bootstrap value), except for Ae. aegypti with moderate to strong support value (73 bootstrap value). All deeper nodes of the phylogeny also had moderate to strong support values, except for the deepest nodes (both 60 bootstrap value). The collapsed branches in the phylogeny show a considerable variation in intraspecific genetic diversity (Fig. 2). Collapsed clades were short for Ae. aegypti and Cx. quinquefasciatus , long for Cx. nigripalpus , Deinocerites sp. and Hg. chrysochlorus , and very long for Ae. taeniorhynchus , indicating variation in the number of mutational steps in each of these clades (see Additional file 1: Fig. S4–9). The genetic distances between the species are given in Additional file 1: Fig. S1. Genetic diversity & Population genetic structure Based on the degree of intraspecific genetic diversity and the species-specific population genetic structure, the six species included in this study fell apart in three different groups. The first group of species, consisting of Ae. aegypti and Cx. quinquefasciatus , has a low genetic diversity, which largely overlaps between the three islands (Fig. 3A and 3B). For these species, the haplotype network analysis revealed a total of three and six unique haplotypes, respectively. Low estimates for the nucleotide diversity ( π ) (0.00296 and 0.00028, resp.) and haplotype diversity ( Hd ) (0.542 and 0.185, resp.) were calculated, compared to the other studied species (Table 3). Regarding the neutrality tests, Tajima’s D was not significant in Ae. aegypti , but negative and significant ( P < 0.05) in Cx. quinquefasciatus . Fu’s F S was positive in Ae. aegypti and negative in Cx. quinquefasciatus , in congruence with Tajima’s D estimate for this species (see Methods for explanation). Aedes aegypti consists of two dominant haplotypes (AE_01 & AE_03), which together comprise all specimens except for one (AE_02). For Cx. quinquefasciatus , one dominant haplotype (QU_01) was found, shared by 47 specimens. Five more haplotypes were found, but these were present only in a single mosquito, differing by only one single substitution from the dominant haplotype. As a result, the haplotype network shows a subtle star-shaped structure. The second species group, consisting of Cx. nigripalpus and Ae. taeniorhynchus , has a high genetic diversity. However, haplotypes did not cluster per island, but rather showed many connections between haplotypes from different islands. For these species, a total of 15 and 29 unique haplotypes, respectively, were resolved (Fig. 3C and 3D). This was supported by the high estimates for the nucleotide diversity (0.00612 and 0.00644, resp.) and haplotype diversity (0.826 and 0.966, resp.), which are much higher than for the first species group (Table 3). Regarding the neutrality tests for these species, Tajima’s D was not significant, and Fu’s F S was negative (see Methods for explanation). For Ae. taeniorhynchus , the haplotype network shows that the majority of the specimens is clustered on the left side of the network (TA_01 to TA_10), but considerable genetic distances are present within the network, even between specimens from the same island. For Cx. nigripalpus , a more complex, partly reticulated network was recovered with five haplotypes found on multiple islands (NI_01, NI_12, NI_19, NI_25, and NI_27). The third species group, consisting of Deinocerites sp. and Hg. chrysochlorus , is characterised by a high genetic diversity. In contrast with the second species group, most haplotypes were found only on a single island. For these species, 16 and 18 unique haplotypes, respectively, were resolved (Fig. 3E and 3F). Additionally, haplotype diversity estimates were high for both species (0.885 and 0.803, resp.). The nucleotide diversity, however, had a high estimate in Deinocerites sp. (0.00606), but a lower estimate for Hg. chrysochlorus (0.00320) (Table 3). Similarly, Tajima’s D was not significant for Deinocerites sp. but negative and significant for Hg. chrysochlorus ( P < 0.05) and Fu’s F S was negative for both species (see Methods for explanation). All haplotypes found for Deinocerites sp. were island-specific and clustered together per island into four groups in the haplotype network: one group with all haplotypes from Aruba (DE_01 to DE_06), two groups with only haplotypes from Curaçao (DE_07 to DE_11 and DE_15 to DE_16), and one group with all haplotypes from Bonaire (DE_12 to DE_14). For Hg. chrysochlorus , all haplotypes were island-specific as well, except for the relatively dominant haplotype (HG_11), which was found on Curaçao and Bonaire. Although population structure in the network was not as distinct as for Deinocerites sp., it shows a distinct cluster of haplotypes from Aruba and a star-shaped structure centred around the dominant haplotype. Discussion The central aim of this study was to explore the potential generalities in variation in mosquito population genetics among a comprehensive assemblage of native and non-native mosquito species. To this end, we investigated the population genetics of an ecologically diverse set of mosquito species from three different Caribbean islands, including both native and non-native species. The haplotype network analysis revealed three groups of species, which differed profoundly in their degree of genetic diversity and population stratification. The populations of Ae. aegypti and Cx. quinquefasciatus , both introduced species, displayed similarly low levels of genetic diversity compared to native mosquitoes, and species with partial overlap in breeding habitat types (e.g., Deinocerites sp. and Hg. chrysochlorus ) were found to have comparable degrees of population stratification. This suggests that the population genetics of mosquitoes vary along both a historical and an ecological axis, thus largely confirming our initial hypothesis. Overall, these results highlight that mosquito population genetics can differ strongly between native and non-native populations, even within a confined area such as the Dutch Leeward Antilles. Among the studied species, both Ae. aegypti and Cx. quinquefasciatus stood out due to their low genetic diversity compared to the four other species. Only three and six haplotypes were found for these two non-native species, respectively, while the native species had almost 20 unique haplotypes on average (Table 3 ). These results from the Americas, together with low estimates for both the nucleotide diversity and the haplotype diversity (especially for Cx. quinquefasciatus ), differ from the much higher levels of genetic diversity found in originally native populations for both species (e.g., Ae. aegypti in Africa [ 73 ] and Cx. quinquefasciatus in India [ 17 , 74 ]). Since both Ae. aegypti and Cx. quinquefasciatus have likely reached the Caribbean in the early 16th century, along with the slave trades to the Americas [ 43 , 44 ], their local populations have had a much shorter period to accumulate mutations, resulting in lower genetic diversity. Furthermore, the haplotype network of Cx. quinquefasciatus (Fig. 3 B) shows a structure consisting of one highly dominant haplotype supplemented by five alternative haplotypes, differing by only a single point mutation from the dominant haplotype. Such a star-shaped structure, together with the significant negative Tajima’s D estimate and negative Fu’s F S estimate (Table 3 ), may indicate a past founder effect for this species. The scarcity of genetic diversity might also be attributed by a past selective sweep, explaining the absence of a star-shaped cluster in the haplotype network of Ae. aegypti (although low sample size cannot be ruled out as potential explanation for the pattern observed here). However, given that selection is much more likely to affect genetically more diverse populations [ 75 ], a founder effect remains more probable if Ae. aegypti populations have never had high genetic diversity on these islands due to their recent colonisation of probably few individuals. These indications of a past founder effect, together with low levels of genetic diversity in relatively young populations, suggest that population history has had an important role in population genetics of these mosquito species. Among the four presumed native species with high genetic diversity the inferred haplotype networks show a marked contrast, supporting a subdivision into two species groups that differ in their ecologies. The haplotype networks of both Cx. nigripalpus and Ae. taeniorhynchus reveal complex reticulation of closely related haplotypes observed on multiple islands. Especially in Cx. nigripalpus , many haplotypes that differed only by a single mutational step were found on neighbouring islands, rather than on the same island, and several haplotypes were present on multiple islands. Additionally, three haplotypes were found (NI_01, NI_25 and TA_03 in Fig. 3 C-D) which were only collected on Aruba and Bonaire, even though these islands are separated by Curaçao on a west-east gradient. In contrast, the haplotypes of Deinocerites sp. and Hg. chrysochlorus mostly cluster together per island. This is especially clear for Deinocerites sp., as all haplotypes of this species were island-specific, and haplotypes most closely related grouped together into four sections in the network (Fig. 3 E), corresponding to the islands from west to east. For Hg. chrysochlorus all haplotypes except the dominant haplotype from Curaçao and Bonaire (Fig. 3 F) were island-specific, similar to the studied species of Deinocerites . This disparity in population genetic structure between these two groups can be contributed to species-specific ecological traits. Both Cx. nigripalpus and Ae. taeniorhynchus breed in a diverse range of dynamic water bodies [ 30 ]. Although the type of temporary water body varies ( Cx. nigripalpus in permanent and temporary freshwater vegetated pools; Ae. taeniorhynchus in coastal marshland, mangroves and beach pools [ 30 , 38 , 42 ]), both species can traverse multiple kilometres to find a bloodmeal and suitable breeding habitat [ 76 , 77 ], and are thus considered strong flyers [ 28 ]. However, Deinocerites sp. and Hg. chrysochlorus are much more specialised regarding their breeding habitat. These species breed in crab holes and tree holes, respectively [ 30 , 42 ], which are closely associated with specific habitats on the islands (mangrove and forest, respectively). As a result, these species are more restricted by fixed ranges within the islands and do not need to disperse each year in search of new breeding habitat. Consequently, such species with clear and narrow niches are less likely to migrate between the islands, leading to a more stratified population genetic structure per island. This subdivision between both groups of native mosquitoes is in congruence with Becker et al. [ 78 ], who distinguished between mosquito species with i) short dispersal ranges (many container breeders), ii) species that can traverse moderate distances, and iii) those that fly long distances between their breeding habitat and the host’s habitat. Both Deinocerites sp. and Hg. chrysochlorus fall into the first category, while Cx. nigripalpus and Ae. taeniorhynchus belong to the third category. Despite Ae. aegypti and Cx. quinquefasciatus being predominantly container breeders (with Cx. quinquefasciatus also found in temporary pools in sparsely vegetated habitat), their short history on the islands hinders direct comparison with the other species, thereby complicating ecological comparisons. This indicates that the population history of non-native species affects the genetic makeup of the population more profoundly than the ecological factors at play, in contrast to locally native species. This will most likely apply to introduced mosquito populations worldwide. The abovementioned contrasts in mosquito population genetics may act as a proxy for differences in the population dynamics and dispersal patterns among different species. A limited dispersal capacity, especially in combination with a specific breeding habitat, may lead to semi-isolated subpopulations of a mosquito species and decrease the chances of interisland dispersal, thus promoting higher levels of genetic diversity and a more stratified genetic population structure. This is illustrated by the haplotype network of Deinocerites sp. (Fig. 3 E), since species in this genus are known to be poor flyers, dispersing not much further than several meters from their crab holes (Van der Kuyp, 1954). The haplotype network of Deinocerites sp. shows very few connections between haplotypes from different islands and exclusively island-specific haplotypes. This implies that interbreeding of individuals from different islands occurs rarely, suggesting interisland dispersal to be highly limited. Conversely, species capable of long-distance dispersal hold the potential to sustain at least some degree of gene flow between subpopulations. For both Cx. nigripalpus , considered a good flyer (2–4 km), and Ae. taeniorhynchus , considered a strong flyer (4 + km) [ 28 ], long-distance dispersal may explain the complexity of their haplotype networks. Since three haplotypes were found on both Aruba and Bonaire but not on Curaçao for these species (NI_01, NI_25, and TA_03 in Fig. 3 C-D), one might assume that dispersal of these species between the islands was not a natural dispersal event. The presence of closely related haplotypes on different islands may have arisen from a combination of both natural wind-mediated long-distance dispersal and random human-mediated dispersal (i.e., through human means of transport such as airplanes or cars [ 27 ]), allowing for local redistribution of mosquitoes of these species within the Dutch Leeward Antilles. Consequently, the sustained high genetic diversity may result from opportunistic breeding habitat selection in newly reached areas, as large parts of the three islands can harbour suitable breeding habitats for these species. Ultimately, this will lead to the formation of subpopulations with gene flow from time to time between the islands. Based on the findings of this study, we propose that the effects of population history, species-specific ecology, and dispersal patterns on the population genetics of mosquitoes are likely not limited to the Dutch Leeward Antilles. The contrasts in population genetics presented here are relevant for many mosquito species that inhabit true islands, or island-like systems. The latter includes mainland mosquito populations, as successful dispersal between hosts and suitable breeding habitat in a patchy landscape is fundamental for many mosquito species. Therefore, differences in ecological niche and dispersal capabilities will presumably be reflected in the population genetic structure of mainland mosquitoes similarly to the studied native species on the Dutch Leeward Antilles. This aligns with broader ecological principles, suggesting that similar patterns may emerge in other fragmented or isolated habitats beyond island environments (e.g., [ 79 ]). Above all, owing to the fundamentality of the factors affecting the investigated mosquito population genetics, our results suggest that the currently biased literature on mosquito population genetics indeed gives an incomplete impression of the stark contrast between locally non-native and native species worldwide. We suggest that a more comparative approach, without focusing solely on the medically relevant species, helps establish a conceptual framework for understanding how dispersal and habitat fragmentation shape mosquito population genetics in diverse ecosystems. Conclusion In line with the discrepancy found in the literature on mosquito population genetics, our data shows considerable differences in the genetic diversity between non-native and native species at a certain location. Moreover, the results show that, within a pool of native species, major differences in population genetic structure may arise from population history and species-specific ecological characteristics (e.g., breeding habitat specificity and dispersal capacity). We hypothesise that similar subdivisions based on introduction history, ecological niche and dispersal capabilities are present globally among mosquito populations, including mainland populations. Abbreviations BIC: Bayesian Information Criterion; bp: Basepairs; COI : Cytochrome c oxidase subunit I; COII : Cytochrome c oxidase subunit II; D : Tajima’s D ; ddH 2 O: Double distilled water; EVS-style trap: Encephalitis Virus Surveillance style trap; F S : Fu’s F S ; H : Number of haplotypes; Hd : Haplotype diversity; min: Minutes; MJN: Median-Joining network; mtDNA: Mitochondrial DNA; ND4 : NADH-ubiquinone oxidoreductase chain 4; ND5 : NADH-ubiquinone oxidoreductase chain 5; NUMTs: Nuclear Mitochondrial DNA segments; π : Nucleotide diversity; PCR: Polymerase chain reaction; S : Number of segregating sites; s: Seconds; tRNA-Leu: tRNA for Leucine; tRNA-Lys: tRNA for Lysine. Declarations Acknowledgements The authors would like to thank the countless individuals who provided assistance locally with information and logistics on the islands. Special thanks go to the local vector control units, notably Luis L. Chong and Ruben Croes from the ‘Yellow Fever and Mosquito Control’ (GKMB) unit of the Public Health Department in Aruba, Gisette Seferina, Roger Nicasia, and Nilerika Zevenhuizen from the Vector Unit of the department of ‘Geneeskunde en Gezondheidszaken’ (G&Gz) of the government of Curaçao, and Joey van Slobbe and Mike Mercuur from the Vector Unit of the Bonaire Public Health Department. Additionally, special thanks are extended to the national parks, particularly Natasha J. Silva and Gian Nunes from the ‘Fundacion Parke Nacional Aruba’ (FPNA), Odette Doest en Erik Houtepen from the ‘Caribbean Research and Management of Biodiversity’ (CARMABI) foundation, and Jilly Sarpong and Monique Grol from ‘Stichting Nationale Parken Bonaire’ (STINAPA Bonaire). Jelle Davelez is thanked for his accompanying and field assistance on Bonaire. The authors are grateful for the assistance of all laboratory technicians involved, particularly for the help of Laurens Stouthart (Naturalis Biodiversity Center), who contributed to shaping and executing the Nanopore sequencing protocol. Furthermore, Ben Wielstra (Institute of Biology, IBL) and Jeremy Miller (Naturalis Biodiversity Center) are sincerely thanked for their input in the interpretation of the results. Anagnostis Theodoropoulos is thanked for his assistance in calculating the population genetic statistics. Funding The mosquitoes (Culicidae) were collected during the 'Expedition ABC Mug-Sangura 2022’, led by researchers from the National Institute for Public Health and the Environment (RIVM) and Naturalis Biodiversity Center. This expedition received financial support from the Dutch Ministry of Health, Welfare, and Sport through the Mosquito-borne Disease Control (MOBOCON) Program [Project number: V/150601/01/PR]. Additionally, this project was supported by the Pandemics and Disaster Preparedness Center (PDPC) as part of the frontrunner project ’Climate Change and Vectorborne Virus Outbreaks. Availability of data and materials All specimens have been collected in local natural park authorities, and research and collection permits can be presented upon request. Specimens were sampled mostly non-destructively, and the vouchers are stored in the Culicidae collection of Naturalis Biodiversity Center, formerly the National Museum of Natural History, Leiden, the Netherlands (RMNH). All sequences, including trace files, are available in the “Caribbean Mosquitoes (CAMOZ)” project on BOLD (www.boldsystems.org) under accession numbers CAMOZ009-23 – CAMOZ363-24. This study analyzed a subset of the data collected during an intensive fieldwork campaign. The complete dataset, which encompasses observations of all other species on the islands, will be published in an taxonomical investigation of the mosquito diversity on the islands. Authors’ contributions PH, MS, KBT and JGvdB designed and conceptualised the project. MAHB and JGvdB were involved in funding acquisition. PH, MAHB, RMW, JGvdB, FS, MS, and AS collected the field data. PH performed the majority of the lab work and data analysis, with the help of JGvdB, MS, and KBT. PH, MS, and JGvdB wrote the manuscript, with input from all authors. All authors have read, contributed to and agreed to the published version of the manuscript. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. References Wilkerson RC, Linton YM & Strickman D. Mosquitoes of the world. Vols. 1 and 2. Baltimore: Johns Hopkins University Press; 2021. ISBN 978-1-421438-14-6. Medlock JM, Hansford KM, Schaffner F, Versteirt V, Hendrickx G, Zeller H et al. A review of the invasive mosquitoes in Europe: ecology, public health risks, and control options. Vector Borne Zoonotic Dis. 2012;12(6):435–447. DOI: 10.1089/vbz.2011.0814 Petrić D, Bellini R, Scholte EJ, Rakotoarivony LM & Schaffner F. Monitoring population and environmental parameters of invasive mosquito species in Europe. Parasit Vectors. 2014;7(187). DOI: 10.1186/1756-3305-7-187 Elbers ARW, Koenraadt CJM & Meiswinkel R. Mosquitoes and Culicoides biting midges: vector range and the influence of climate change. Rev Sci Tech Off Int Epiz. 2015;34(1):123–137. DOI: 10.20506/rst.34.1.2349 Mwingira V, Mboera LEG, Dicke M & Takken W. Exploiting the chemical ecology of mosquito oviposition behavior in mosquito surveillance and control: a review. J Vector Ecol. 2020;45(2):155–179. DOI: 10.1111/jvec.12387 Renault D, Derocles SAP, Haubrock P, Simard F, Cuthbert RN & Valiente-Moro C. Biological, ecological and trophic features of invasive mosquitoes and other hematophagous arthropods: what makes them successful? Biol Invasions. 2024;26:33–55. DOI: 10.1007/s10530-023-03158-5 Fonseca DM, Widdel AK, Hutchinson M, Spichiger SE & Kramer LD. Fine-scale spatial and temporal population genetics of Aedes japonicus , a new US mosquito, reveal multiple introductions. Mol Ecol. 2010;19:1559–1572. DOI: 10.1111/j.1365-294X.2010.04576.x Urdaneta-Marquez L & Failloux AB. Population genetic structure of Aedes aegypti , the principal vector of dengue viruses. Infect Genet Evol. 2011;11:253–261. DOI: 10.1016/j.meegid.2010.11.020 Janssen N, Werner D & Kampen H. Population genetics of the invasive Asian bush mosquito Aedes japonicus (Diptera, Culicidae) in Germany–a re-evaluation in a time period of separate populations merging. Parasitol Res. 2019;118:2475–2484. DOI: 10.1007/s00436-019-06376-w Li SP, Jiang F, Lu H, Kang X, Wang YH, Zou Z et al. Mosquito diversity and population genetic structure of six mosquito species from Hainan Island. Front Genet. 2020;11:602863. DOI: 10.3389/fgene.2020.602863 Choi KS, Koekemoer LL & Coetzee M. Population genetic structure of the major malaria vector Anopheles funestus s.s. and allied species in southern Africa. Parasit Vectors. 2012;5:283. DOI: 10.1186/1756-3305-5-283 Sunil S, Singh OP, Nanda N, Raghavendra K, Niranjan Reddy BP & Subbarao SK. Analysis of population genetic structure of Indian Anopheles culicifacies species A using microsatellite markers. Parasit Vectors. 2013;6:166. DOI: 10.1186/1756-3305-6-166 Wilke ABB, Oliveira Vidal P, Suesdek L & Toledo Marrelli M. Population genetics of neotropical Culex quinquefasciatus (Diptera: Culicidae). Parasit Vectors. 2014;7:468. DOI: 10.1186/s13071-014-0468-8 Bunmee K, Thaenkham U, Saralamba N, Ponlawat A, Zhong DB, Cui LW et al. Population genetic structure of the malaria vector Anopheles minimus in Thailand based on mitochondrial DNA markers. Parasit Vectors. 2021;14:496. DOI: 10.1186/s13071-021-04998-7 Gao J, Zhang HD, Guo XX, Xing D, Dong YD, Lan CJ et al. Dispersal patterns and population genetic structure of Aedes albopictus (Diptera: Culicidae) in three different climatic regions of China. Parasit Vectors. 2021;14:12. DOI: 10.1186/s13071-020-04521-4 Shin J & Jung J. Comparative population genetics of the invasive mosquito Aedes albopictus and the native mosquito Aedes flavopictus in the Korean peninsula. Parasit Vectors. 2021;14:377. DOI: 10.1186/s13071-021-04873-5 Fonseca DM, Smith JL, Wilkerson RC & Fleischer RC. Pathways of expansion and multiple introductions illustrated by large genetic differentiation among worldwide populations of the southern house mosquito. Am J Trop Med Hyg. 2006;74(2):284–289. Szalanski AL, Owens CB, Lewter JA & Broce AB. Genetic structure of Aedes vexans (Diptera: Culicidae) populations from central United States based on mitochondrial ND5 sequences. Ann Entomol Soc Am. 2006;99(1):157–163. DOI: 10.1603/0013-8746(2006)099[0157:GSOAVD]2.0.CO;2 Hasan AU, Suguri S, Ahmed SMU, Fujimoto C, Harada M, Rahman SM et al. Molecular phylogeography of Culex quinquefasciatus mosquitoes in central Bangladesh. Acta Trop. 2009;112:106–114. DOI: 10.1016/j.actatropica.2009.07.005 Morais SA, de Almeida F, Suesdek L & Marrelli MT. Low genetic diversity in Wolbachia -infected Culex quinquefasciatus (Diptera: Culicidae) from Brazil and Argentina. Rev Inst Med Trop Sao Paulo. 2012;54(6):325–329. Low VL, Lim PE, Chen CD, Lim YAL, Tan TK, Norma-Rashid Y et al. Mitochondrial DNA analyses reveal low genetic diversity in Culex quinquefasciatus from residential areas in Malaysia. Med Vet Entomol. 2014;28:157–168. DOI: 10.1111/mve.12022 Sherpa S, Rioux D, Goindin D, Fouque F, François O & Després L. At the origin of a worldwide invasion: unraveling the genetic makeup of the Caribbean bridgehead populations of the dengue vector Aedes aegypti . Genome Biol Evol. 2017;10(1):56–71. DOI: 10.1093/gbe/evx267 Sherpa S, Rioux D, Pougnet-Lagarde C & Després L. Genetic diversity and distribution differ between long-established and recently introduced populations in the invasive mosquito Aedes albopictus . Infect Genet Evol. 2018;58:145–156. DOI: 10.1016/j.meegid.2017.12.018 Hasan AU, Suguri S, Fujimoto C, Itaki RL, Harada M, Kawabata M et al. Genetic diversity in two sibling species of the Anopheles punctulatus group of mosquitoes on Guadalcanal in the Solomon Islands. BMC Evol Biol. 2008;8:318. DOI: 10.1186/1471-2148-8-318 Bataille A, Cunningham AA, Cedeño V, Patiño L, Constantinou A, Kramer LD et al. Natural colonization and adaptation of a mosquito species in Galápagos and its implications for disease threats to endemic wildlife. Proc Natl Acad Sci U S A. 2009;106(25):10230–10235. DOI: 10.1073/pnas.0901308106 Panda D & Barik TK. Molecular characterization and genetic divergence of seven Culex mosquito (Diptera: Culicidae) species using Mt COI gene from Odisha state, India. J Basic Appl Zool. 2022;83:41. DOI: 10.1186/s41936-022-00305-7 Service MW. Mosquito (Diptera: Culicidae) dispersal: the long and short of it. J Med Entomol. 1997;34(6):579–588. Verdonschot PFM & Besse-Lototskaya AA. Flight distance of mosquitoes (Culicidae): a metadata analysis to support the management of barrier zones around rewetted and newly constructed wetlands. Limnologica. 2014;45:69–79. DOI: 10.1016/j.limno.2013.11.002 Debrot AO, Henkens RJHG & Verweij PJFM. Staat van de natuur van Caribisch Nederland 2017: een eerste beoordeling van de staat (van instandhouding), bedreigingen en managementimplicaties van habitats en soorten in Caribisch Nederland. Rapport Co86/17. Wageningen: Wageningen Marine Research; 2018. Van der Kuyp E. Mosquitoes of the Netherlands Antilles and their hygienic importance. Stud. Fauna Curaçao. 1954;5:37–114. Martinez C, Goddard L, Kushnir Y & Ting MF. Seasonal climatology and dynamical mechanisms of rainfall in the Caribbean. Clim Dynam. 2019;53:825–846. DOI: 10.1007/s00382-019-04616-4 KNMI: hour data Caribbean area; 2023. https://www.knmi.nl/nederland-nu/klimatologie/uurgegevens_Caribisch_gebied. Accessed 12 Oct 2023. NU.CW; 2022. https://nu.cw/2022/11/03/nog-meer-regen-voor-de-abc-eilanden/. Accessed 15 Nov 2022. Johnston E, Weinstein P, Slaney D, Flies AS, Fricker S & Williams C. Mosquito communities with trap height and urban-rural gradient in Adelaide, South Australia: implications for disease vector surveillance. J Vector Ecol. 2014;39(1):48–55. DOI: 10.1111/j.1948-7134.2014.12069.x European Centre for Disease Prevention and Control; European Food Safety Authority. Field sampling methods for mosquitoes, sandflies, biting midges and ticks: VectorNet project 2014–2018. Stockholm and Parma: ECDC and EFSA; 2018. Lane J. Neotropical Culicidae. Vol. I and II. São Paulo: University of São Paulo; 1953. Pratt HD. Key to the Culicidae of Puerto Rico. 1969. Belkin JN, Heinemann SJ & Page WA. The Culicidae of Jamaica (Mosquito Studies. XXI). Contrib Am Entomol Inst. 1970;6:1–458. Darsie RF, Scott Taylor D, Prusak ZA & Verna TN. Checklist of the mosquitoes of the Bahamas with three additions to its fauna and keys to the adult females and fourth instars. J Am Mosq Control Assoc. 2010;26(2):127–134. DOI: 10.2987/09-5982.1 Burkett-Cadena ND. Mosquitoes of the Southeastern United States. Tuscaloosa: The University of Alabama Press; 2013. Van der Beek JG, Dijkstra KDB, Van der Hoorn BB, Boerlijst SP, Busscher L, Kok ML et al. Taxonomy, ecology and distribution of the mosquitoes (Diptera: Culicidae) of the Dutch Leeward Islands, with a key to the adults and fourth instar larvae. Contrib Zool. 2020;89:373–392. DOI: 10.1163/18759866-bja10005 Arnell JH. Mosquito studies (Diptera, Culicidae) XXXII: a revision of the genus Haemagogus . Contrib Am Entomol Inst. 1973;10(2):1–174. Belkin JN. The mosquitoes of the South Pacific (Diptera: Culicidae). Vols. 1 and 2. California: University of California Press; 1962. Powell JR & Tabachnick WJ. History of domestication and spread of Aedes aegypti : a review. Mem Inst Oswaldo Cruz. 2013;108(1):11–17. DOI: 10.1590/0074-0276130395 Oshaghi MA. mtDNA inheritance in the mosquitoes of Anopheles stephensii . Mitochondrion. 2005;5:266–271. DOI: 10.1016/j.mito.2005.05.001 Moore WS. Inferring phylogenies from mtDNA variation: mitochondrial-gene trees versus nuclear-gene trees. Evolution. 1995;49(4):718–726. Rubinoff D, Cameron S & Will K. A genomic perspective on the shortcomings of mitochondrial DNA for “barcoding” identification. J Hered. 2006;97(6):581–594. DOI: 10.1093/jhered/esl036 Zink RM & Barrowclough GF. Mitochondrial DNA under siege in avian phylogeography. Mol Ecol. 2008;17:2107–2121. DOI: 10.1111/j.1365-294X.2008.03737.x Trimbos KB, Doorenweerd C, Kraaijeveld K, Musters CJM, Groen NM, de Knijff P et al. Patterns in nuclear and mitochondrial DNA reveal historical and recent isolation in the Black-Tailed Godwit ( Limosa limosa ). PLoS One. 2014;9(1):e83949. DOI: 10.1371/journal.pone.0083949 Chan A, Chiang LP, Hapuarachchi HC, Tan CH, Pang SC, Lee R et al. DNA barcoding: complementing morphological identification of mosquito species in Singapore. Parasit Vectors. 2014;7(569). DOI: 10.1186/s13071-014-0569-4 Hernández-Triana LM, Brugman VA, Pramual P, Barrero E, Nikilova NI, Ruiz-Arrondo I et al. Genetic diversity and population structure of Culex modestus across Europe: does recent appearance in the United Kingdom reveal a tendency for geographical spread? Med Vet Entomol. 2014. DOI: 10.1111/mve.12412. Le Goff G, Boussès P, Julienne S, Brengues C, Rahola N, Rocamora G et al. The mosquitoes (Diptera: Culicidae) of Seychelles: taxonomy, ecology, vectorial importance, and identification keys. Parasit Vectors. 2012;5(207). DOI: 10.1186/1756-3305-5-207 Knobloch EC & Schmidt RC: Non-destructively barcoding hundreds of freshwater macroinvertebrates with a MinION; 2022. https://www.protocols.io/view/non-destructively-barcoding-hundreds-of-freshwater-cbh6sj9e.html. Accessed 1 Jan 2023. Bergsten J, Brilmyer G, Crampton-Platt A & Nilsson AN. Sympatry and colour variation disguised well-differentiated sister species: Suphrodytes revised with integrative taxonomy including 5 kbp of housekeeping genes (Coleoptera: Dytiscidae). DNA Barcodes. 2012;1:1–18. DOI: 10.2478/dna-2012-0001 Cristiano MP, Fernandes-Salomão TM & Yotoko KSC. Nuclear mitochondrial DNA: an Achilles’ heel of molecular systematics, phylogenetics, and phylogeographic studies of stingless bees. Apidologie. 2012;43:527–538. DOI: 10.1007/s13592-012-0122-4 Wang YH, Zhao Y, Bollas A, Wang Y & Au KF. Nanopore sequencing technology, bioinformatics and applications. Nat Biotechnol. 2021;39:1348–1365. DOI: 10.1038/s41587-021-01108-x Okonechnikov K, Golosova O, Fursov M, the UGENE team. Unipro UGENE: a unified bioinformatics toolkit. Bioinformatics. 2012;28:1166–1167. DOI:10.1093/bioinformatics/bts091 Edgar RC. MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics. 2004;5:113. DOI: 10.1186/1471-2105-5-113 Leigh JW, Bryant D & Steel M. popart documentation: Data Input. Otago, University of Otago; 2023. https://popart.maths.otago.ac.nz/documentation/. Accessed 12 May 2023. BOLD. BOLD: The Barcode of Life Data System. Mol Ecol Notes. 2007. www.boldsystems.org Leigh JW & Bryant D. popart: full-feature software for haplotype network construction. Methods Ecol Evol. 2015;6:1110–1116. https://popart.maths.otago.ac.nz/ DOI: 10.1111/2041-210X.12410 Bandelt H, Forster P & Röhl A. Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol. 1999;16(1):37–38. Clement M, Snell Q, Walke P, Posada D & Crandall K. TCS: estimating gene genealogies. Proc 16 IPDPS. 2002;2:184. Rozas J, Ferrer-Mata A, Sánchez-DelBarrio JC, Guirao-Rico S, Librado P, Ramos-Onsins SE et al. DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol Biol Evol. 2017;34(12):3299–3302. DOI: 10.1093/molbev/msx248 Tajima F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics. 1989;123:585–595. Fu YX. Statistical tests of neutrality of mutations against population growth, hitchhiking and background selection. Genetics. 1997;147:915–925. Sharma M, Fomda BA, Mazta S, Sehgal R, Singh BB & Malla N. Genetic diversity and population genetic structure analysis of Echinococcus granulosus sensu stricto complex based on mitochondrial DNA signature. PLoS One. 2013;8(12):e82904. DOI: 10.1371/journal.pone.0082904 Minh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD, von Haeseler A et al. IQ-Tree 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol Biol Evol. 2020;37(5):1530–1534. DOI: 10.1093/molbev/msaa015 Kalyaanamoorthy S, Minh BQ, Wong TFK, von Haeseler A & Jermiin LS. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat Methods. 2017;14(6):587–589. DOI: 10.1038/nmeth.4285 Hoang DT, Chernomor O, von Haeseler A, Minh BQ & Vinh LS. UFBoot2: improving the ultrafast bootstrap approximation. Mol Biol Evol. 2017;35(2):518–522. DOI: 10.1093/molbev/msx281 Yu GC, Smith DK, Zhu HC, Guan Y & Lam TTY. ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods Ecol Evol . 2017;8:28–36. DOI: 10.1111/2041-210x.12628 Revell LJ. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol Evol. 2012;3:217–223. DOI: 10.1111/j.2041-210X.2011.00169.x Gloria-Soria A, Ayala D, Bheecarry A, Calderon-Arguedas O, Chadee DD, Chiappero M et al. Global genetic diversity of Aedes aegypti . Mol Ecol. 2016;25:5377–5395. DOI: 10.1111/mec.13866 Valdivalagan C, Karthika P, Murugan K, Panneerselvam C, Del Serrone P & Benelli G. Exploring genetic variation in haplotypes of the filariasis vector Culex quinquefasciatus (Diptera: Culicidae) through DNA barcoding. Acta Trop. 2017;169:43–50. DOI: 10.1016/j.actatropica.2017.01.020 Birader K. Genetic Diversity and the Adaptation of Species to Changing Environments. J Biodivers Endanger Species. 2023;11:474. Provost MW. The dispersal of Aedes taeniorhynchus . 1. Preliminary studies. Mosq News. 1952;12(3):174–190. Horsfall RB. Mosquitoes: their bionomics and relation to disease. New York: The Ronald Press Company; 1955. Becker N, Petrić D, Zgomba M, Boase C, Madon MB, Dahl C et al. Biology of mosquitoes. In: Mosquitoes. Fascinating Life Sciences, pp 11–27. Cham: Springer Nature; 2020. DOI: 10.1007/978-3-030-11623-1_2 Laurance WF. Beyond island biogeography theory: understanding habitat fragmentation in the real. In: The Theory of Island Biogeography Revisited, edited by Losos JB and Ricklefs RE, pp. 214–236. Princeton: Princeton University Press; 2010. DOI: 10.1515/9781400831920.214 Liu H & Beckenbach AT. Evolution of the mitochondrial cytochrome oxidase II gene among 10 orders of insects. Mol Phylogenet Evol. 1992;1:41–52. DOI: 10.1016/1055-7903(92)90034-e Tables Table 1 List of primer sets used per species with primer details. Species Primer set (reference) Primer sequence (5’-3’) T a (°C) Ae. aegypti F: SCTL2-J-3037 [80] ATGGCAGATTAGTGCAATGA 47 R: Ae-COII-R [25] GATTTAAGAGATCATTACTTGC Ae. taeniorhynchus F: SCTL2-J-3037 ATGGCAGATTAGTGCAATGA 47 R: Ae-COII-R GATTTAAGAGATCATTACTTGC Cx. nigripalpus F: SCTL2-J-3037 ATGGCAGATTAGTGCAATGA 47 R: Cul-COII-R (†) GRTTTAAGAGAYCAKTACTTGC Cx. quinquefasciatus F: SCTL2-J-3037 ATGGCAGATTAGTGCAATGA 45 R: TK-N-3785 [80] GTTTAAGAGACCAGTACTTG Deinocerites sp. F: SCTL2-J-3037 ATGGCAGATTAGTGCAATGA 47 R: Cul-COII-R (†) GRTTTAAGAGAYCAKTACTTGC Hg. chrysochlorus F: SCTL2-J-3037 ATGGCAGATTAGTGCAATGA 47 R: Cul-COII-R (†) GRTTTAAGAGAYCAKTACTTGC (†) Newly developed reverse primer for this study. Table 2 Total numbers of specimens per island and per species included in the present study. Note that the total number of locations is not equal to the sum of either the number of locations per species or the number of locations per island, since a number of specimens from different species were sampled at the same location, for example in a BG Pro Trap. Species n Aruba ( n locations ) n Curaçao ( n locations ) n Bonaire ( n locations ) n total ( n locations ) Ae. aegypti 6 ( 4 ) 7 ( 4 ) 7 ( 4 ) 20 ( 12 ) Ae. taeniorhynchus 12 ( 7 ) 13 ( 7 ) 13 ( 7 ) 38 ( 21 ) Cx. nigripalpus 21 ( 8 ) 18 ( 7 ) 19 ( 6 ) 58 ( 21 ) Cx. quinquefasciatus 21 ( 12 ) 17 ( 9 ) 14 ( 8 ) 52 ( 29 ) Deinocerites sp. 23 ( 7 ) 16 ( 4 ) 15 ( 4 ) 54 ( 15 ) Hg. chrysochlorus 2 ( 1 ) 13 ( 8 ) 21 ( 13 ) 36 ( 22 ) Total 85 ( 39 ) 84 ( 39 ) 89 ( 42 ) 258 ( 108 ) Table 3 Summary of the population genetic statistics of the mitochondrial COII sequences for all six studied species. For each species: the number of sequences included in the calculation ( COII ), the number of haplotypes ( H ), the number of segregating or polymorphic sites ( S ), the nucleotide diversity ( π ), the haplotype diversity ( Hd ), the standard error of the haplotype diversity ( s (Hd) ), estimated Tajima’s D ( D ), the p-value for the estimated Tajima’s D ( P (D) ), and estimated Fu’s F S ( F S ). Significance shown as * P <0.5 or NS (not significant). Species COII H S π Hd s (Hd) D P (D) F S Ae. aegypti 20 3 5 0.00296 0.542 0.076 1.31665 NS 3.244 Cx. quinquefasciatus 52 6 5 0.00028 0.185 0.072 -1.98592 * -6.970 Cx. nigripalpus 58 29 28 0.00644 0.966 0.009 -1.04344 NS -16.792 Ae. taeniorhynchus 38 15 22 0.00612 0.826 0.050 -0.67506 NS -3.188 Deinocerites sp. 54 16 18 0.00606 0.885 0.024 0.15591 NS -2.636 Hg. chrysochlorus 36 18 21 0.00320 0.803 0.068 -1.92392 * -13.105 Additional Declarations No competing interests reported. Supplementary Files HellemanetalMSParasitesVectorsSUPPLEMENTARY.docx Supplementary information Additional file 1: Table S1. Preliminary list of mosquito species collected on Aruba, Curaçao and Bonaire, during the 2022 expedition. Fig. S1. Total haplotype network of all 258 COII sequences included in this study using TCS inference. Fig. S2. All collection localities of specimens included in this study for Aedes aegypti , Aedes taeniorhynchus , and Haemagogus chrysochlorus . Fig. S3. All collection localities of specimens included in this study for Culex quinquefasciatus , Culex nigripalpus , and Deinocerites sp. Fig. S4. Maximum Likelihood tree of the 20 included Aedes aegypti sequences (684 bp) in this study, showing internal branching and branch lengths of the collapsed clade from Fig. 2. Fig. S5. Maximum Likelihood tree of the 38 included Aedes taeniorhynchus sequences (684 bp) in this study, showing internal branching and branch lengths of the collapsed clade from Fig. 2. Fig. S6. Maximum Likelihood tree of the 58 included Culex nigripalpus sequences (684 bp) in this study, showing internal branching and branch lengths of the collapsed clade from Fig. 2. Fig. S7. Maximum Likelihood tree of the 52 included Culex quinquefasciatus sequences (684 bp) in this study, showing internal branching and branch lengths of the collapsed clade from Fig. 2. Fig. S8. Maximum Likelihood tree of the 54 included Deinocerites sp. sequences (684 bp) in this study, showing internal branching and branch lengths of the collapsed clade from Fig. 2. Fig. S9. Maximum Likelihood tree of the 36 included Haemagogus chrysochlorus sequences (684 bp) in this study, showing internal branching and branch lengths of the collapsed clade from Fig. 2. Cite Share Download PDF Status: Published Journal Publication published 09 May, 2025 Read the published version in Parasites & Vectors → Version 1 posted Editorial decision: Revision requested 02 Dec, 2024 Reviews received at journal 26 Nov, 2024 Reviews received at journal 12 Nov, 2024 Reviewers agreed at journal 25 Oct, 2024 Reviewers agreed at journal 24 Oct, 2024 Reviewers agreed at journal 24 Oct, 2024 Reviewers invited by journal 22 Oct, 2024 Editor assigned by journal 15 Oct, 2024 Submission checks completed at journal 15 Oct, 2024 First submitted to journal 12 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-5250794","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":385288256,"identity":"f19296a5-4500-4992-8063-15b79463df1f","order_by":0,"name":"Pepijn Helleman","email":"","orcid":"","institution":"Leiden University","correspondingAuthor":false,"prefix":"","firstName":"Pepijn","middleName":"","lastName":"Helleman","suffix":""},{"id":385288257,"identity":"f8fde253-8f2c-4b0c-b52c-faa0f19388cf","order_by":1,"name":"Maarten Schrama","email":"","orcid":"","institution":"Leiden University","correspondingAuthor":false,"prefix":"","firstName":"Maarten","middleName":"","lastName":"Schrama","suffix":""},{"id":385288258,"identity":"9328232e-18dd-43d7-af4f-c6d76156899f","order_by":2,"name":"Krijn B. Trimbos","email":"","orcid":"","institution":"Leiden University","correspondingAuthor":false,"prefix":"","firstName":"Krijn","middleName":"B.","lastName":"Trimbos","suffix":""},{"id":385288259,"identity":"52df84ff-1ff2-473e-ab8f-f9b44552b3d8","order_by":3,"name":"Marieta A.H. Braks","email":"","orcid":"","institution":"National Institute for Public Health and the Environment","correspondingAuthor":false,"prefix":"","firstName":"Marieta","middleName":"A.H.","lastName":"Braks","suffix":""},{"id":385288260,"identity":"c1da4fcf-96be-4a52-b71d-f1fcdc71c5a3","order_by":4,"name":"Francis Schaffner","email":"","orcid":"","institution":"Francis Schaffner Consultancy","correspondingAuthor":false,"prefix":"","firstName":"Francis","middleName":"","lastName":"Schaffner","suffix":""},{"id":385288261,"identity":"b613ef71-4d2f-4993-a51c-f8f07ce0f99b","order_by":5,"name":"Arjan Stroo","email":"","orcid":"","institution":"Centre for Monitoring of Vectors (CMV), Netherlands Food and Consumer Product Safety Authority (NVWA)","correspondingAuthor":false,"prefix":"","firstName":"Arjan","middleName":"","lastName":"Stroo","suffix":""},{"id":385288262,"identity":"f4029311-966f-4669-871e-80c137613ea8","order_by":6,"name":"Roel M. Wouters","email":"","orcid":"","institution":"Naturalis Biodiversity Center","correspondingAuthor":false,"prefix":"","firstName":"Roel","middleName":"M.","lastName":"Wouters","suffix":""},{"id":385288263,"identity":"0e004505-a780-4955-948f-9fcb04a54c91","order_by":7,"name":"Jordy G. van der Beek","email":"data:image/png;base64,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","orcid":"","institution":"Leiden University","correspondingAuthor":true,"prefix":"","firstName":"Jordy","middleName":"G. van der","lastName":"Beek","suffix":""}],"badges":[],"createdAt":"2024-10-12 09:53:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5250794/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5250794/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13071-025-06801-3","type":"published","date":"2025-05-09T15:57:04+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":72333989,"identity":"bb0819f3-ef08-4c67-a3e7-580747119201","added_by":"auto","created_at":"2024-12-25 15:29:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1749822,"visible":true,"origin":"","legend":"\u003cp\u003eSample locations and island sections used in this study. Coloured dots represent sample locations for all mosquito specimens from which sequences were obtained for the six studied species. Colour of each dot represents the applied sampling method. ‘Adult else’ encompasses adult mosquitoes collected by human landing catches or by netting. Sample locations in close proximity are presented in concentric circles. Depicted sections are the equally sized island sections which were created for mosquito subsampling in this study. Dashed lines indicate that the distance between islands is not to scale. Inset in top right corner shows location of the islands within the Caribbean, 30-80 km off the coast of Venezuela. Basemap source: ESRI.\u003c/p\u003e","description":"","filename":"HellemanetalPVFigure1submission.png","url":"https://assets-eu.researchsquare.com/files/rs-5250794/v1/7529987103887570612a5bd6.png"},{"id":72333988,"identity":"62e2e03b-3a31-4955-b826-7c755ba15bd6","added_by":"auto","created_at":"2024-12-25 15:29:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":146621,"visible":true,"origin":"","legend":"\u003cp\u003eUnrooted Maximum Likelihood tree of the 258 included Caribbean mosquito sequences (684 bp). Branch length corresponds with the genetic distance between sequences. Branching below the species level is shown as triangular ‘collapsed’ branches. Collapsed branch size corresponds with the internal branch lengths of the clade, and the triangles were scaled to 50% for readability. Support values represent 1000 Ultrafast bootstraps (%).\u003c/p\u003e","description":"","filename":"HellemanetalPVFigure2submission.png","url":"https://assets-eu.researchsquare.com/files/rs-5250794/v1/577df8128cf60e0757d23c51.png"},{"id":72333990,"identity":"b0700b0b-e516-4d43-8b80-0b069207a6f3","added_by":"auto","created_at":"2024-12-25 15:29:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1469775,"visible":true,"origin":"","legend":"\u003cp\u003eHaplotype network analysis of \u003cem\u003eCOII\u003c/em\u003e sequences using Median-Joining Network inference for (\u003cstrong\u003ea\u003c/strong\u003e) \u003cem\u003eAedes aegypti\u003c/em\u003e, (\u003cstrong\u003eb\u003c/strong\u003e) \u003cem\u003eCulex quinquefasciatus\u003c/em\u003e, (\u003cstrong\u003ec\u003c/strong\u003e) \u003cem\u003eCulex nigripalpus\u003c/em\u003e, (\u003cstrong\u003ed\u003c/strong\u003e) \u003cem\u003eAedes taeniorhynchus\u003c/em\u003e, (\u003cstrong\u003ee\u003c/strong\u003e) \u003cem\u003eDeinocerites\u003c/em\u003e sp., and (\u003cstrong\u003ef\u003c/strong\u003e) \u003cem\u003eHaemagogus chrysochlorus\u003c/em\u003e. Pie charts represent unique haplotypes found in this study, with pie chart size representing the number of sequences with the same haplotype and pie chart colours corresponding to the island of origin of the sequences (pink: Aruba; yellow: Curaçao; blue: Bonaire). Hatch marks on the edges represent the number of genetic differences between closely related sequences.\u003c/p\u003e","description":"","filename":"HellemanetalPVFigure3submission.png","url":"https://assets-eu.researchsquare.com/files/rs-5250794/v1/4c36621d4cba4401594cef68.png"},{"id":82537457,"identity":"8c95f597-f818-49ce-bbf8-a4535fb2b558","added_by":"auto","created_at":"2025-05-12 16:06:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4032594,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5250794/v1/26241f4f-cd51-4680-9248-25c7ee672e70.pdf"},{"id":72333992,"identity":"8c8b43a3-1ff5-426d-9c51-b4eb3281af77","added_by":"auto","created_at":"2024-12-25 15:29:03","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2330535,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional file 1: Table S1.\u003c/strong\u003e Preliminary list of mosquito species collected on Aruba, Curaçao and Bonaire, during the 2022 expedition. \u003cstrong\u003eFig. S1.\u003c/strong\u003e Total haplotype network of all 258 \u003cem\u003eCOII\u003c/em\u003e sequences included in this study using TCS inference. \u003cstrong\u003eFig. S2.\u003c/strong\u003e All collection localities of specimens included in this study for \u003cem\u003eAedes aegypti\u003c/em\u003e, \u003cem\u003eAedes taeniorhynchus\u003c/em\u003e, and \u003cem\u003eHaemagogus chrysochlorus\u003c/em\u003e. \u003cstrong\u003eFig. S3.\u003c/strong\u003e All collection localities of specimens included in this study for \u003cem\u003eCulex quinquefasciatus\u003c/em\u003e, \u003cem\u003eCulex nigripalpus\u003c/em\u003e, and \u003cem\u003eDeinocerites\u003c/em\u003e sp. \u003cstrong\u003eFig. S4.\u003c/strong\u003e Maximum Likelihood tree of the 20 included \u003cem\u003eAedes aegypti\u003c/em\u003e sequences (684 bp) in this study, showing internal branching and branch lengths of the collapsed clade from Fig. 2. \u003cstrong\u003eFig. S5.\u003c/strong\u003e Maximum Likelihood tree of the 38 included \u003cem\u003eAedes taeniorhynchus\u003c/em\u003esequences (684 bp) in this study, showing internal branching and branch lengths of the collapsed clade from Fig. 2. \u003cstrong\u003eFig. S6.\u003c/strong\u003e Maximum Likelihood tree of the 58 included \u003cem\u003eCulex nigripalpus\u003c/em\u003esequences (684 bp) in this study, showing internal branching and branch lengths of the collapsed clade from Fig. 2. \u003cstrong\u003eFig. S7.\u003c/strong\u003e Maximum Likelihood tree of the 52 included \u003cem\u003eCulex quinquefasciatus\u003c/em\u003esequences (684 bp) in this study, showing internal branching and branch lengths of the collapsed clade from Fig. 2. \u003cstrong\u003eFig. S8.\u003c/strong\u003e Maximum Likelihood tree of the 54 included \u003cem\u003eDeinocerites\u003c/em\u003e sp. sequences (684 bp) in this study, showing internal branching and branch lengths of the collapsed clade from Fig. 2. \u003cstrong\u003eFig. S9.\u003c/strong\u003e Maximum Likelihood tree of the 36 included \u003cem\u003eHaemagogus chrysochlorus\u003c/em\u003esequences (684 bp) in this study, showing internal branching and branch lengths of the collapsed clade from Fig. 2.\u003c/p\u003e","description":"","filename":"HellemanetalMSParasitesVectorsSUPPLEMENTARY.docx","url":"https://assets-eu.researchsquare.com/files/rs-5250794/v1/793feb69c044f3f61e0fa4f5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The ecological niche and population history shape mosquito population genetics: a case study from Caribbean islands","fulltext":[{"header":"Background","content":"\u003cp\u003eGlobally, there are approximately 3,700 species of mosquitoes (Diptera: Culicidae) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Although much is known about the ecology and distribution of a limited number of species, most notably the species of medical importance (e.g., [\u003cspan additionalcitationids=\"CR3 CR4 CR5\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]), the majority of species is greatly understudied. Similarly, mosquito population dynamics and structure have been studied using population genetics almost exclusively in relation to pathogen transmission and vector control (e.g., [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]). As a result, the scarce information on mosquito population genetics that is currently available, is mostly based on a small subset of mosquito biodiversity, representing only a small fraction of the ecological diversity among mosquitoes. These well-studied, medically relevant species are often introduced outside of their native range and therefore globally widespread (e.g., [\u003cspan additionalcitationids=\"CR12 CR13 CR14\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]), which likely coincides with a particular pattern in population genetic structure [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Hence, it remains unclear how population genetics of mosquitoes vary among native species with different ecological strategies, and whether these patterns differ from introduced well-studied species.\u003c/p\u003e \u003cp\u003eEmerging evidence demonstrates that commonly introduced species, such as \u003cem\u003eCulex quinquefasciatus\u003c/em\u003e Say, 1823 and \u003cem\u003eAedes aegypti\u003c/em\u003e (Linnaeus, 1762), exhibit noticeable differences in both ecology as well as population genetic structure compared to native species. Recent studies often find a reduction in genetic diversity among introduced mosquito populations outside their native range compared to their source populations, which often display a much higher degree of genetic diversity (e.g., [\u003cspan additionalcitationids=\"CR17 CR18 CR19 CR20 CR21 CR22\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]). In contrast, among the few studies on locally native species there are notable observations of local radiation and speciation (e.g., in the \u003cem\u003eAnopheles punctulatus\u003c/em\u003e group on the Solomon Islands [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], in the \u003cem\u003eAe. taeniorhynchus\u003c/em\u003e (Wiedemann, 1821) population on the Gal\u0026aacute;pagos Islands [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], and in \u003cem\u003eCx. fuscanus\u003c/em\u003e Wiedemann, 1820 populations in India, [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]). These observations of local radiation indicate a potential contrast between the well-studied non-native and the understudied local mosquito species, suggesting profoundly different patterns in population genetic structure among these groups. Studying the population genetics of a variety of mosquito species in a single area allows for direct comparison of the population genetic structure of different species in relation to their behaviour and ecology, since the species studied will have been subjected to similar macro-environmental conditions. Hence, to elucidate how natural variation in population genetics relates to mosquito species ecology, patterns in genetic structure need to be studied across a more diverse assemblage of mosquito species in a single area.\u003c/p\u003e \u003cp\u003eFor this purpose, islands of moderate size offer compelling model systems due to several advantages. Such islands provide the opportunity to sample populations across their entire local distribution, presenting a more complete and reliable representation of the overall population structure. Moreover, the surrounding ocean likely isolates the islands from most natural colonisation events by mosquitoes [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The Dutch Leeward Antilles, comprising Aruba, Cura\u0026ccedil;ao, and Bonaire, provide an ideal study case to investigate the variation in mosquito population genetics, due to the presence of a patchy mosaic of various distinct habitat types on these islands (e.g., [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]) in combination with a rich local mosquito fauna consisting of both native and non-native species [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe objective of this study is to explore the variation in mosquito population genetics by comparing the genetic diversity and population genetic structure among a comprehensive assemblage of native and non-native mosquito species. By analysing both native and non-native mosquito species with a broad range of ecological niches, we aim to gain new insights on the role of species-specific ecology in mosquito population genetics. We hypothesise that, in a given area, population genetics of mosquitoes differ between native and non-native populations along both a historical and an ecological axis. More specifically, we expect 1) species with a stricter ecological niche to comprise more unique haplotypes, because their populations are more easily fragmented when suitable habitat has a patchy spatial distribution, and 2) that non-native species exhibit a much smaller genetic radiation, resulting from less time to accumulate new mutations. To achieve the objectives, we used mitochondrial \u003cem\u003eCOII\u003c/em\u003e (or \u003cem\u003eCOX2\u003c/em\u003e, cytochrome c oxidase subunit 2) sequences to perform haplotype network analysis, supported by phylogenetic analysis, for six diverse species of mosquitoes in the southern Caribbean.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy site\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVariation in genetic diversity and population genetic structure among ecologically diverse mosquito species was explored on the islands of Aruba, Curaçao, and Bonaire in November and early December 2022 (Fig. 1), during the ‘Expedition ABC Mug-Sangura 2022’. Aruba (180 km\u003csup\u003e2\u003c/sup\u003e) and Bonaire (288 km\u003csup\u003e2\u003c/sup\u003e) were sampled for six days, while Curaçao, a slightly larger island (444 km\u003csup\u003e2\u003c/sup\u003e), was sampled for eight days. The mosquito samples used in the genetic analysis were obtained from the larger collections made during this expedition. Some additional samples from Bonaire were obtained from the ‘Naturalis Relay Expedition 2022-2023’, collected between 1-14 December 2022. The islands are located in the southern Caribbean Sea, approximately 30 to 80 km off the coast of Venezuela, and follow a west to east gradient, with Aruba and Curaçao approx. 80 km apart and Curaçao and Bonaire approx. 45 km apart (Fig. 1). All three islands have a semi-arid tropical savannah climate and offer a rich diversity of habitats, including dry tropical forests, streams, freshwater and saltwater lakes, mangroves, caves, rocky and sandy shores, as well as various urban habitats [29]. The fieldwork was carried out during the late rainy season, which typically lasts from October to December/January on the islands [31], with heavy rainfalls during the months preceding the fieldwork [32, 33], likely causing high densities of mosquitoes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSampling strategy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mosquitoes included in this study were sampled using a variety of trapping methods to increase the chances of collecting both individuals with common and rare haplotypes among local populations. Adult mosquitoes were trapped using CO\u003csub\u003e2\u003c/sub\u003e-baited BG Pro traps (Biogents, Regensburg, Germany), which were set up in 31 locations (Fig. 1) during daytime and emptied the next morning. The traps were used as EVS-style traps by hanging them approximately 100 cm [34] above the ground in a sheltered place (e.g., within vegetation). CO\u003csub\u003e2\u003c/sub\u003e was generated through sugar fermentation, utilizing a mixture of beet sugar, active-dry yeast, yeast nutrient salt, and tap water. Additionally, 24 locations (Fig. 1) were sampled for adult mosquitoes through human landing catches or by catching flying and resting mosquitoes with a net and aspirator. Larval sampling was performed by primarily using 350 ml Mosquito Dippers (BioQuip Products, Rancho Dominguez, California); smaller water bodies were sampled with turkey basters, soup spoons, or manual hand suction pumps [35]. Larval samples were taken from a diverse range of water bodies (n=53), such as ponds, lakes, seashore water bodies, streams, rainwater puddles, rock pools, crab holes, bromeliads, tree holes and artificial containers. Mosquitoes were collected from different areas on the islands, both coastal and inland regions, aiming for a wide coverage of the entire islands (Fig. 1). Suitable terrestrial and aquatic sampling sites were identified on sight or selected based on arial maps and expertise of local collaborators.\u003c/p\u003e\n\u003cp\u003eUpon collection, live specimens were put in the freezer for at least 20 minutes prior to morphological identification. Identification was done morphologically with an unpublished identification key for the islands, which was constructed based on existing literature and keys for the region ([30, 36 – 41]). After identification, specimens were stored in 70% ethanol and several undamaged adult specimens were mounted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTaxon selection \u0026amp; specimen selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo obtain reliable insights into the local variation in mosquito population structure and genetic diversity on the islands, species were selected according to the following three criteria: they i) were among the most abundant species on the islands, ii) occupied different ecological niches, and iii) constituted a mix of native and non-native mosquito species. Of the 16 species of mosquitoes recorded during the expedition (Additional file 1: Table S1), nine species were observed only on a single island, or in a limited number of locations, and were consequently excluded from further analysis. Based on the criteria, specimens of six species were included in this study, which represent a variety of ecological strategies: \u003cem\u003eAe. aegypti\u003c/em\u003e, \u003cem\u003eAe. taeniorhynchus\u003c/em\u003e, \u003cem\u003eCx. nigripalpus\u003c/em\u003e Theobald, 1901, \u003cem\u003eCx. quinquefasciatus\u003c/em\u003e, a currently undescribed species of \u003cem\u003eDeinocerites\u003c/em\u003e, and \u003cem\u003eHaemagogus chrysochlorus\u003c/em\u003e Arnell, 1973. The native species include two species breeding in dynamic and temporary water bodies (\u003cem\u003eCx. nigripalpus\u003c/em\u003e, breeding in temporary freshwater bodies, and \u003cem\u003eAe. taeniorhynchus\u003c/em\u003e, breeding in coastal temporary water bodies), and two species with highly specialised breeding habitats (\u003cem\u003eDeinocerites\u003c/em\u003e sp., breeding in crab burrows in the mangrove, and \u003cem\u003eHg. chrysochlorus\u003c/em\u003e, breeding in tree holes) [30, 38, 42]. The non-native species \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. quinquefasciatus\u003c/em\u003e are opportunistic container breeders with a strong association to urban areas [30, 38]. Both are considered to have invaded and colonised the Caribbean in the 16\u003csup\u003eth\u003c/sup\u003e century [43, 44].\u003c/p\u003e\n\u003cp\u003eThe aim was to include between 30-60 specimens per species in total for genetic analysis. To ensure a geographical spread of data points on each island, specimens were randomly subsampled from eight sections per island. A polygons for each island was manually created, before being divided into eight equally large sections by performing K-means clustering in QGIS (version 3.28. 2 Firenze) on a random point layer (100.000 points) within the island polygon. By creating Voronoi polygons and taking the intersect with the island polygon, new polygons for eight equally large sections per island were created (Fig. 1). For each island section, a sample location was selected with the \u003cem\u003esample()\u003c/em\u003e function in a basic randomiser script in RStudio (version 2022.12.0 Build 353; R version 4.2.1). From every selected location, three specimens were taken, preferably adult samples as adult DNA extractions had significantly higher success rates than larval extractions during a DNA extraction pilot in the lab. If fewer than three specimens of a given species were collected at a selected location, additional specimens were randomly subsampled to obtain three specimens per species per island section, aiming for an even distribution of the number of specimens per island section. Ultimately, the total number of specimens differed per species or islands, because of locally low abundance of some species on specific islands, or technical difficulties during the extraction or sequencing phase (Table 2).\u003c/p\u003e\n\u003cp\u003eThe specimens are all vouchered and stored in the Culicidae collection of Naturalis Biodiversity Center, formerly the National Museum of Natural History, Leiden, the Netherlands (RNMH).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNA extraction and amplification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo elucidate patterns in the population genetics of local mosquito populations, mitochondrial DNA (mtDNA) was used. Since the haploid mitogenome is exclusively inherited maternally [45], the effective population size is four times smaller than in nuclear DNA, resulting in faster lineage sorting [46 – 48]. Theoretically, this enables mtDNA to reflect changes in population structure on shorter time scales [49], increasing chances of detecting changes in population structure. Based on an unpublished dataset of mitochondrial genomes of Dutch mosquitoes, four genes were compared regarding their intraspecific variability. Compared to \u003cem\u003eCOI\u003c/em\u003e (used in [50, 51]), \u003cem\u003eND4\u003c/em\u003e (used in [52]), and \u003cem\u003eND5\u003c/em\u003e (used in [25]), the \u003cem\u003eCOII\u003c/em\u003e gene (used in [25]) showed the highest intraspecific genetic diversity.\u003c/p\u003e\n\u003cp\u003eExtractions on adult specimens were carried out using a single leg, which was rinsed with ddH\u003csub\u003e2\u003c/sub\u003eO for 10 minutes and dried (adapted from [53]). DNA extraction was performed using 20 μl Lucigen QuickExtract DNA Extraction Solution (Lucigen, Middleton, Wisconsin), following the manufacturer’s protocol with the following adaptations: the first incubation at 65°C for 15 minutes, and the second incubation at 98°C for 2 minutes. For larval specimens, 1-2 segments cut from the abdomen were used, or the entire abdomen for tiny larvae. Larval DNA extraction had low success rates using Lucigen QuickExtract and was therefore performed using the Higher Purity Tissue DNA purification kit (Canvax Biotech, Valladolid, Spain), following the protocol of the manufacturer. DNA of \u003cem\u003eCx. quinquefasciatus\u003c/em\u003e larvae was extracted using a DNeasy Blood \u0026amp; Tissue kit (QIAGEN, Hilden, Germany) following the manufacturer’s protocol, with the adaptation of using 50 μl of provided Buffer AE for DNA elution. The Canvax and QIAGEN kits had similar DNA yields. Samples were stored at -20°C.\u003c/p\u003e\n\u003cp\u003eEach PCR reaction was prepared with 2.0 μl of DNA extract, 17.5 μl of Hot Start Taq 2X Master Mix (New England Biolabs, Ipswich, Massachusetts), 1.4 μl (10 μM stock) of forward and reverse primer, and 12.7 μl of nuclease-free water, adding up to a volume of 35 μl per reaction. The three primer sets used varied for different species (Table 1), but all targeted the same 745 bp locus. One newly developed reverse primer was utilized during this study (Cul-COII-R, see Table 1). The forward primer annealing site was located in tRNA-Leu DNA, and the reverse primer annealing site was in tRNA-Lys, resulting in an amplicon that included the \u003cem\u003eCOII\u003c/em\u003e gene. The PCR protocol was the same for all three primer sets, except for the annealing temperature (see Table 1): 30 s of initial denaturation at 95°C, followed by 35 cycles of 30 s denaturation at 95°C, 30 s annealing, and 1 min extension at 68°C, concluded with 5 min final extension at 68°C. All PCR products were checked on 1%-agarose gels, before sending out for Sanger sequencing.\u003c/p\u003e\n\u003cp\u003eThe Sanger-sequencing data of \u003cem\u003eAe. taeniorhynchus\u003c/em\u003e specimens contained multiple conflicting base calls in specific positions in the forward and reverse sequences, potentially resulting from Nuclear Mitochondrial DNA segments (NUMTs, see [54] and [55]. To eliminate ambiguities, all samples of this species were sequenced again using Oxford Nanopore sequencing [56]. Nanopore sequences a single DNA fragment, allowing us to analyse the individual reads at locations that otherwise returned double peaks in the chromatogram derived from Sanger sequencing. During the first PCR, the ONT-CO2F/ONT-Ae-COII-R primers were used (F-primer: 5’-TTTCTGTTGGTGCTGATATTGCATGGCAGATTAGTGCAATGA-3’ and R-primer: 5’-ACTTGCCTGTCGCTCTATCTTCGATTTAAGAGATCATTACTTGC-3’), followed by a second PCR using the Oxford EXP-PBC096 Barcode kit and LongAmp Taq 2X master mix. Every PCR was followed by sample quality checks on E-Gel and tapestation and a bead-clean-up with MN-beads. After end-repair, another MN-bead clean-up, and ligation of the Sequencing Adapters with the Oxford SQK-LSK114 Ligation Sequencing Kit v14, the DNA was loaded onto a Flongle flow cell for sequencing using Oxford GridION.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSequence alignment and analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaw sequences were trimmed and aligned in Unipro Ugene software (version 45.1; [57]) to obtain full sequences of the \u003cem\u003eCOII\u003c/em\u003e marker gene (684 bp). Sequences with many ambiguities were excluded from the analysis. Finalised sequences were aligned using the MUSCLE default algorithm [58] and converted to Nexus-format text-files as described by Leigh et al. [59]. All finalised sequences are available in the “Caribbean Mosquitoes (CAMOZ)” project on BOLD [60] under accession numbers CAMOZ009-23 – CAMOZ363-24.\u003c/p\u003e\n\u003cp\u003eHaplotype network analysis was performed using PopART software (version 1.7; [61]) to infer genealogical relationships among the studied specimens. Haplotype networks were plotted per species using the Median-Joining network (MJN) inference method [62]. The number of haplotypes (\u003cem\u003eH\u003c/em\u003e) and the number of segregating sites (\u003cem\u003eS\u003c/em\u003e) were also retrieved from PopART. Additionally, all species were plotted in a single haplotype network (Additional file 1: Fig. S1) using the TCS method [63], which reduced the formation of complex knots in between species in the network.\u003c/p\u003e\n\u003cp\u003eIn addition to haplotype network analysis, DnaSP software (version 6.12; [64]) was used to calculate the nucleotide diversity (\u003cem\u003eπ\u003c/em\u003e), haplotype diversity (\u003cem\u003eHd\u003c/em\u003e), Tajima’s D, and Fu’s F\u003csub\u003eS\u003c/sub\u003e per species. Tajima’s \u003cem\u003eD\u003c/em\u003e estimates if mutations occur due to neutral evolution or selective pressures by taking the difference between observed and expected nucleotide diversity [65]. Fu’s F\u003csub\u003eS\u003c/sub\u003e statistic is a similar neutrality test like Tajima’s \u003cem\u003eD\u003c/em\u003e, but uses the haplotype distribution [66]. Since these statistics are both influenced by changes in population size, it can be used to detect past population expansions. Negative values for both neutrality tests represent an excess frequency of rare polymorphisms or alleles, indicative of recent population expansion or genetic hitchhiking [67]. Two positions were masked for \u003cem\u003eAe. aegypti\u003c/em\u003e sequences in PopART and DnaSP, due to ambiguous base calls. To support the results from the haplotype network analysis, a phylogenetic analysis including all successful sequences was performed. IQ-Tree2 [68] was used to calculate a Maximum Likelihood tree, using standard model selection with ModelFinder [69] and 1000 Ultrafast bootstraps [70]. The TPM2u+F+G4 was selected as best-fit model according to the BIC value by ModelFinder. Intraspecific branching is depicted as a triangular radiation (henceforth referred to as ‘collapsed’ branching). A wider triangle represents longer internal branch lengths in the respective collapsed clade. Branch length represents genetic distance between specimens. Support values are given per node as bootstrap values (%). The calculated tree was visualised using packages \u003cem\u003eggtree\u003c/em\u003e (version 3.10.0; [71]) and \u003cem\u003ephytools\u003c/em\u003e (version 2.0-3; [72]) in R (version 2023.12.0 Build 369; R version 4.3.2).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eMosquito collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn total, \u003cem\u003eCOII\u003c/em\u003e sequences of 258 mosquitoes belonging to six species were successfully obtained during this study (Table 2). Sequences were obtained from mosquitoes collected from a total of 108 different sampling locations (all species combined), with a wide geographical coverage of each island, and each species was collected on all three islands (Fig. 1 and Additional file 1: Fig. S2-3). Roughly equal numbers of specimens were used from each island for all species except \u003cem\u003eHg. chrysochlorus\u003c/em\u003e, which was found only in a single location in Aruba.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhylogenetic relationships\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll clades at species level were resolved as monophyletic, confirming that the included species are indeed genetically well separated populations with likely no gene flow between the species studied (Fig. 2). All clades had strong support values (≥90 bootstrap value), except for \u003cem\u003eAe. aegypti\u003c/em\u003e with moderate to strong support value (73 bootstrap value). All deeper nodes of the phylogeny also had moderate to strong support values, except for the deepest nodes (both 60 bootstrap value). The collapsed branches in the phylogeny show a considerable variation in intraspecific genetic diversity (Fig. 2). Collapsed clades were short for \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. quinquefasciatus\u003c/em\u003e, long for \u003cem\u003eCx. nigripalpus\u003c/em\u003e, \u003cem\u003eDeinocerites\u003c/em\u003e sp. and \u003cem\u003eHg. chrysochlorus\u003c/em\u003e, and very long for \u003cem\u003eAe. taeniorhynchus\u003c/em\u003e, indicating variation in the number of mutational steps in each of these clades (see Additional file 1: Fig. S4–9). The genetic distances between the species are given in Additional file 1: Fig. S1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenetic diversity \u0026amp; Population genetic structure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the degree of intraspecific genetic diversity and the species-specific population genetic structure, the six species included in this study fell apart in three different groups. The first group of species, consisting of \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. quinquefasciatus\u003c/em\u003e, has a low genetic diversity, which largely overlaps between the three islands (Fig. 3A and 3B). For these species, the haplotype network analysis revealed a total of three and six unique haplotypes, respectively. Low estimates for the nucleotide diversity (\u003cem\u003eπ\u003c/em\u003e) (0.00296 and 0.00028, resp.) and haplotype diversity (\u003cem\u003eHd\u003c/em\u003e) (0.542 and 0.185, resp.) were calculated, compared to the other studied species (Table 3). Regarding the neutrality tests, Tajima’s \u003cem\u003eD\u003c/em\u003e was not significant in \u003cem\u003eAe. aegypti\u003c/em\u003e, but negative and significant (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) in \u003cem\u003eCx. quinquefasciatus\u003c/em\u003e. Fu’s \u003cem\u003eF\u003csub\u003eS\u003c/sub\u003e\u003c/em\u003e was positive in \u003cem\u003eAe. aegypti\u003c/em\u003e and negative in \u003cem\u003eCx. quinquefasciatus\u003c/em\u003e, in congruence with Tajima’s \u003cem\u003eD\u003c/em\u003e estimate for this species (see Methods for explanation). \u003cem\u003eAedes aegypti\u003c/em\u003e consists of two dominant haplotypes (AE_01 \u0026amp; AE_03), which together comprise all specimens except for one (AE_02). For \u003cem\u003eCx. quinquefasciatus\u003c/em\u003e, one dominant haplotype (QU_01) was found, shared by 47 specimens. Five more haplotypes were found, but these were present only in a single mosquito, differing by only one single substitution from the dominant haplotype. As a result, the haplotype network shows a subtle star-shaped structure.\u003c/p\u003e\n\u003cp\u003eThe second species group, consisting of \u003cem\u003eCx. nigripalpus\u003c/em\u003e and \u003cem\u003eAe. taeniorhynchus\u003c/em\u003e, has a high genetic diversity. However, haplotypes did not cluster per island, but rather showed many connections between haplotypes from different islands. For these species, a total of 15 and 29 unique haplotypes, respectively, were resolved (Fig. 3C and 3D). This was supported by the high estimates for the nucleotide diversity (0.00612 and 0.00644, resp.) and haplotype diversity (0.826 and 0.966, resp.), which are much higher than for the first species group (Table 3). Regarding the neutrality tests for these species, Tajima’s \u003cem\u003eD\u003c/em\u003e was not significant, and Fu’s \u003cem\u003eF\u003csub\u003eS\u003c/sub\u003e\u003c/em\u003e was negative (see Methods for explanation). For \u003cem\u003eAe. taeniorhynchus\u003c/em\u003e, the haplotype network shows that the majority of the specimens is clustered on the left side of the network (TA_01 to TA_10), but considerable genetic distances are present within the network, even between specimens from the same island. For \u003cem\u003eCx. nigripalpus\u003c/em\u003e, a more complex, partly reticulated network was recovered with five haplotypes found on multiple islands (NI_01, NI_12, NI_19, NI_25, and NI_27).\u003c/p\u003e\n\u003cp\u003eThe third species group, consisting of \u003cem\u003eDeinocerites\u003c/em\u003e sp. and \u003cem\u003eHg. chrysochlorus\u003c/em\u003e, is characterised by a high genetic diversity. In contrast with the second species group, most haplotypes were found only on a single island. For these species, 16 and 18 unique haplotypes, respectively, were resolved (Fig. 3E and 3F). Additionally, haplotype diversity estimates were high for both species (0.885 and 0.803, resp.). The nucleotide diversity, however, had a high estimate in \u003cem\u003eDeinocerites\u003c/em\u003e sp. (0.00606), but a lower estimate for \u003cem\u003eHg. chrysochlorus\u003c/em\u003e (0.00320) (Table 3). Similarly, Tajima’s \u003cem\u003eD\u003c/em\u003e was not significant for \u003cem\u003eDeinocerites\u003c/em\u003e sp. but negative and significant for \u003cem\u003eHg. chrysochlorus\u003c/em\u003e (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) and Fu’s \u003cem\u003eF\u003csub\u003eS\u003c/sub\u003e\u003c/em\u003e was negative for both species (see Methods for explanation). All haplotypes found for \u003cem\u003eDeinocerites\u003c/em\u003e sp. were island-specific and clustered together per island into four groups in the haplotype network: one group with all haplotypes from Aruba (DE_01 to DE_06), two groups with only haplotypes from Curaçao (DE_07 to DE_11 and DE_15 to DE_16), and one group with all haplotypes from Bonaire (DE_12 to DE_14). For \u003cem\u003eHg. chrysochlorus\u003c/em\u003e, all haplotypes were island-specific as well, except for the relatively dominant haplotype (HG_11), which was found on Curaçao and Bonaire. Although population structure in the network was not as distinct as for \u003cem\u003eDeinocerites\u003c/em\u003e sp., it shows a distinct cluster of haplotypes from Aruba and a star-shaped structure centred around the dominant haplotype.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe central aim of this study was to explore the potential generalities in variation in mosquito population genetics among a comprehensive assemblage of native and non-native mosquito species. To this end, we investigated the population genetics of an ecologically diverse set of mosquito species from three different Caribbean islands, including both native and non-native species. The haplotype network analysis revealed three groups of species, which differed profoundly in their degree of genetic diversity and population stratification. The populations of \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. quinquefasciatus\u003c/em\u003e, both introduced species, displayed similarly low levels of genetic diversity compared to native mosquitoes, and species with partial overlap in breeding habitat types (e.g., \u003cem\u003eDeinocerites\u003c/em\u003e sp. and \u003cem\u003eHg. chrysochlorus\u003c/em\u003e) were found to have comparable degrees of population stratification. This suggests that the population genetics of mosquitoes vary along both a historical and an ecological axis, thus largely confirming our initial hypothesis. Overall, these results highlight that mosquito population genetics can differ strongly between native and non-native populations, even within a confined area such as the Dutch Leeward Antilles.\u003c/p\u003e \u003cp\u003eAmong the studied species, both \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. quinquefasciatus\u003c/em\u003e stood out due to their low genetic diversity compared to the four other species. Only three and six haplotypes were found for these two non-native species, respectively, while the native species had almost 20 unique haplotypes on average (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These results from the Americas, together with low estimates for both the nucleotide diversity and the haplotype diversity (especially for \u003cem\u003eCx. quinquefasciatus\u003c/em\u003e), differ from the much higher levels of genetic diversity found in originally native populations for both species (e.g., \u003cem\u003eAe. aegypti\u003c/em\u003e in Africa [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e] and \u003cem\u003eCx. quinquefasciatus\u003c/em\u003e in India [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]). Since both \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. quinquefasciatus\u003c/em\u003e have likely reached the Caribbean in the early 16th century, along with the slave trades to the Americas [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], their local populations have had a much shorter period to accumulate mutations, resulting in lower genetic diversity. Furthermore, the haplotype network of \u003cem\u003eCx. quinquefasciatus\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) shows a structure consisting of one highly dominant haplotype supplemented by five alternative haplotypes, differing by only a single point mutation from the dominant haplotype. Such a star-shaped structure, together with the significant negative Tajima\u0026rsquo;s \u003cem\u003eD\u003c/em\u003e estimate and negative Fu\u0026rsquo;s \u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003eS\u003c/em\u003e\u003c/sub\u003e estimate (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), may indicate a past founder effect for this species. The scarcity of genetic diversity might also be attributed by a past selective sweep, explaining the absence of a star-shaped cluster in the haplotype network of \u003cem\u003eAe. aegypti\u003c/em\u003e (although low sample size cannot be ruled out as potential explanation for the pattern observed here). However, given that selection is much more likely to affect genetically more diverse populations [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e], a founder effect remains more probable if \u003cem\u003eAe. aegypti\u003c/em\u003e populations have never had high genetic diversity on these islands due to their recent colonisation of probably few individuals. These indications of a past founder effect, together with low levels of genetic diversity in relatively young populations, suggest that population history has had an important role in population genetics of these mosquito species.\u003c/p\u003e \u003cp\u003eAmong the four presumed native species with high genetic diversity the inferred haplotype networks show a marked contrast, supporting a subdivision into two species groups that differ in their ecologies. The haplotype networks of both \u003cem\u003eCx. nigripalpus\u003c/em\u003e and \u003cem\u003eAe. taeniorhynchus\u003c/em\u003e reveal complex reticulation of closely related haplotypes observed on multiple islands. Especially in \u003cem\u003eCx. nigripalpus\u003c/em\u003e, many haplotypes that differed only by a single mutational step were found on neighbouring islands, rather than on the same island, and several haplotypes were present on multiple islands. Additionally, three haplotypes were found (NI_01, NI_25 and TA_03 in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-D) which were only collected on Aruba and Bonaire, even though these islands are separated by Cura\u0026ccedil;ao on a west-east gradient. In contrast, the haplotypes of \u003cem\u003eDeinocerites\u003c/em\u003e sp. and \u003cem\u003eHg. chrysochlorus\u003c/em\u003e mostly cluster together per island. This is especially clear for \u003cem\u003eDeinocerites\u003c/em\u003e sp., as all haplotypes of this species were island-specific, and haplotypes most closely related grouped together into four sections in the network (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE), corresponding to the islands from west to east. For \u003cem\u003eHg. chrysochlorus\u003c/em\u003e all haplotypes except the dominant haplotype from Cura\u0026ccedil;ao and Bonaire (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF) were island-specific, similar to the studied species of \u003cem\u003eDeinocerites\u003c/em\u003e. This disparity in population genetic structure between these two groups can be contributed to species-specific ecological traits. Both \u003cem\u003eCx. nigripalpus\u003c/em\u003e and \u003cem\u003eAe. taeniorhynchus\u003c/em\u003e breed in a diverse range of dynamic water bodies [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Although the type of temporary water body varies (\u003cem\u003eCx. nigripalpus\u003c/em\u003e in permanent and temporary freshwater vegetated pools; \u003cem\u003eAe. taeniorhynchus\u003c/em\u003e in coastal marshland, mangroves and beach pools [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]), both species can traverse multiple kilometres to find a bloodmeal and suitable breeding habitat [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e], and are thus considered strong flyers [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, \u003cem\u003eDeinocerites\u003c/em\u003e sp. and \u003cem\u003eHg. chrysochlorus\u003c/em\u003e are much more specialised regarding their breeding habitat. These species breed in crab holes and tree holes, respectively [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], which are closely associated with specific habitats on the islands (mangrove and forest, respectively). As a result, these species are more restricted by fixed ranges within the islands and do not need to disperse each year in search of new breeding habitat. Consequently, such species with clear and narrow niches are less likely to migrate between the islands, leading to a more stratified population genetic structure per island.\u003c/p\u003e \u003cp\u003eThis subdivision between both groups of native mosquitoes is in congruence with Becker et al. [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e], who distinguished between mosquito species with i) short dispersal ranges (many container breeders), ii) species that can traverse moderate distances, and iii) those that fly long distances between their breeding habitat and the host\u0026rsquo;s habitat. Both \u003cem\u003eDeinocerites\u003c/em\u003e sp. and \u003cem\u003eHg. chrysochlorus\u003c/em\u003e fall into the first category, while \u003cem\u003eCx. nigripalpus\u003c/em\u003e and \u003cem\u003eAe. taeniorhynchus\u003c/em\u003e belong to the third category. Despite \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. quinquefasciatus\u003c/em\u003e being predominantly container breeders (with \u003cem\u003eCx. quinquefasciatus\u003c/em\u003e also found in temporary pools in sparsely vegetated habitat), their short history on the islands hinders direct comparison with the other species, thereby complicating ecological comparisons. This indicates that the population history of non-native species affects the genetic makeup of the population more profoundly than the ecological factors at play, in contrast to locally native species. This will most likely apply to introduced mosquito populations worldwide.\u003c/p\u003e \u003cp\u003eThe abovementioned contrasts in mosquito population genetics may act as a proxy for differences in the population dynamics and dispersal patterns among different species. A limited dispersal capacity, especially in combination with a specific breeding habitat, may lead to semi-isolated subpopulations of a mosquito species and decrease the chances of interisland dispersal, thus promoting higher levels of genetic diversity and a more stratified genetic population structure. This is illustrated by the haplotype network of \u003cem\u003eDeinocerites\u003c/em\u003e sp. (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE), since species in this genus are known to be poor flyers, dispersing not much further than several meters from their crab holes (Van der Kuyp, 1954). The haplotype network of \u003cem\u003eDeinocerites\u003c/em\u003e sp. shows very few connections between haplotypes from different islands and exclusively island-specific haplotypes. This implies that interbreeding of individuals from different islands occurs rarely, suggesting interisland dispersal to be highly limited. Conversely, species capable of long-distance dispersal hold the potential to sustain at least some degree of gene flow between subpopulations. For both \u003cem\u003eCx. nigripalpus\u003c/em\u003e, considered a good flyer (2\u0026ndash;4 km), and \u003cem\u003eAe. taeniorhynchus\u003c/em\u003e, considered a strong flyer (4\u0026thinsp;+\u0026thinsp;km) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], long-distance dispersal may explain the complexity of their haplotype networks. Since three haplotypes were found on both Aruba and Bonaire but not on Cura\u0026ccedil;ao for these species (NI_01, NI_25, and TA_03 in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-D), one might assume that dispersal of these species between the islands was not a natural dispersal event. The presence of closely related haplotypes on different islands may have arisen from a combination of both natural wind-mediated long-distance dispersal and random human-mediated dispersal (i.e., through human means of transport such as airplanes or cars [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]), allowing for local redistribution of mosquitoes of these species within the Dutch Leeward Antilles. Consequently, the sustained high genetic diversity may result from opportunistic breeding habitat selection in newly reached areas, as large parts of the three islands can harbour suitable breeding habitats for these species. Ultimately, this will lead to the formation of subpopulations with gene flow from time to time between the islands.\u003c/p\u003e \u003cp\u003eBased on the findings of this study, we propose that the effects of population history, species-specific ecology, and dispersal patterns on the population genetics of mosquitoes are likely not limited to the Dutch Leeward Antilles. The contrasts in population genetics presented here are relevant for many mosquito species that inhabit true islands, or island-like systems. The latter includes mainland mosquito populations, as successful dispersal between hosts and suitable breeding habitat in a patchy landscape is fundamental for many mosquito species. Therefore, differences in ecological niche and dispersal capabilities will presumably be reflected in the population genetic structure of mainland mosquitoes similarly to the studied native species on the Dutch Leeward Antilles. This aligns with broader ecological principles, suggesting that similar patterns may emerge in other fragmented or isolated habitats beyond island environments (e.g., [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]).\u003c/p\u003e \u003cp\u003eAbove all, owing to the fundamentality of the factors affecting the investigated mosquito population genetics, our results suggest that the currently biased literature on mosquito population genetics indeed gives an incomplete impression of the stark contrast between locally non-native and native species worldwide. We suggest that a more comparative approach, without focusing solely on the medically relevant species, helps establish a conceptual framework for understanding how dispersal and habitat fragmentation shape mosquito population genetics in diverse ecosystems.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn line with the discrepancy found in the literature on mosquito population genetics, our data shows considerable differences in the genetic diversity between non-native and native species at a certain location. Moreover, the results show that, within a pool of native species, major differences in population genetic structure may arise from population history and species-specific ecological characteristics (e.g., breeding habitat specificity and dispersal capacity). We hypothesise that similar subdivisions based on introduction history, ecological niche and dispersal capabilities are present globally among mosquito populations, including mainland populations.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBIC: Bayesian Information Criterion; bp: Basepairs; \u003cem\u003eCOI\u003c/em\u003e: Cytochrome c oxidase subunit I; \u003cem\u003eCOII\u003c/em\u003e: Cytochrome c oxidase subunit II; \u003cem\u003eD\u003c/em\u003e: Tajima\u0026rsquo;s \u003cem\u003eD\u003c/em\u003e; ddH\u003csub\u003e2\u003c/sub\u003eO: Double distilled water; EVS-style trap: Encephalitis Virus Surveillance style trap; \u003cem\u003eF\u003csub\u003eS\u003c/sub\u003e\u003c/em\u003e: Fu\u0026rsquo;s \u003cem\u003eF\u003csub\u003eS\u003c/sub\u003e\u003c/em\u003e; \u003cem\u003eH\u003c/em\u003e: Number of haplotypes; \u003cem\u003eHd\u003c/em\u003e: Haplotype diversity; min: Minutes; MJN: Median-Joining network; mtDNA: Mitochondrial DNA; \u003cem\u003eND4\u003c/em\u003e: NADH-ubiquinone oxidoreductase chain 4; \u003cem\u003eND5\u003c/em\u003e: NADH-ubiquinone oxidoreductase chain 5; NUMTs: Nuclear Mitochondrial DNA segments; \u003cem\u003e\u0026pi;\u003c/em\u003e: Nucleotide diversity; PCR: Polymerase chain reaction; \u003cem\u003eS\u003c/em\u003e: Number of segregating sites; s: Seconds; tRNA-Leu: tRNA for Leucine; tRNA-Lys: tRNA for Lysine.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the countless individuals who provided assistance locally with information and logistics on the islands. Special thanks go to the local vector control units, notably Luis L. Chong and Ruben Croes from the \u0026lsquo;Yellow Fever and Mosquito Control\u0026rsquo; (GKMB) unit of the Public Health Department in Aruba, Gisette Seferina, Roger Nicasia, and Nilerika Zevenhuizen from the Vector Unit of the department of \u0026lsquo;Geneeskunde en Gezondheidszaken\u0026rsquo; (G\u0026amp;Gz) of the government of Cura\u0026ccedil;ao, and Joey van Slobbe and Mike Mercuur from the Vector Unit of the Bonaire Public Health Department. Additionally, special thanks are extended to the national parks, particularly Natasha J. Silva and Gian Nunes from the \u0026lsquo;Fundacion Parke Nacional Aruba\u0026rsquo; (FPNA), Odette Doest en Erik Houtepen from the \u0026lsquo;Caribbean Research and Management of Biodiversity\u0026rsquo; (CARMABI) foundation, and Jilly Sarpong and Monique Grol from \u0026lsquo;Stichting Nationale Parken Bonaire\u0026rsquo; (STINAPA Bonaire). Jelle Davelez is thanked for his accompanying and field assistance on Bonaire. The authors are grateful for the assistance of all laboratory technicians involved, particularly for the help of Laurens Stouthart (Naturalis Biodiversity Center), who contributed to shaping and executing the Nanopore sequencing protocol. Furthermore, Ben Wielstra (Institute of Biology, IBL) and Jeremy Miller (Naturalis Biodiversity Center) are sincerely thanked for their input in the interpretation of the results. Anagnostis Theodoropoulos is thanked for his assistance in calculating the population genetic statistics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mosquitoes (Culicidae) were collected during the \u0026apos;Expedition ABC Mug-Sangura 2022\u0026rsquo;,\u0026nbsp;led by researchers from the National Institute for Public Health and the Environment (RIVM) and Naturalis Biodiversity Center. This expedition received financial support from the Dutch Ministry of Health, Welfare, and Sport through the Mosquito-borne Disease Control (MOBOCON) Program [Project number: V/150601/01/PR]. Additionally, this project was supported by the Pandemics and Disaster Preparedness Center (PDPC) as part of the frontrunner project \u0026rsquo;Climate Change and Vectorborne Virus Outbreaks.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll specimens have been collected in local natural park authorities, and research and collection permits can be presented upon request. Specimens were sampled mostly non-destructively, and the vouchers are stored in the Culicidae collection of Naturalis Biodiversity Center, formerly the National Museum of Natural History, Leiden, the Netherlands (RMNH). All sequences, including trace files, are available in the \u0026ldquo;Caribbean Mosquitoes (CAMOZ)\u0026rdquo; project on BOLD (www.boldsystems.org) under accession numbers CAMOZ009-23 \u0026ndash; CAMOZ363-24. This study analyzed a subset of the data collected during an intensive fieldwork campaign. The complete dataset, which encompasses observations of all other species on the islands, will be published in an taxonomical investigation of the mosquito diversity on the islands.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePH, MS, KBT and JGvdB designed and conceptualised the project. MAHB and JGvdB were involved in funding acquisition. PH, MAHB, RMW, JGvdB, FS, MS, and AS collected the field data. PH performed the majority of the lab work and data analysis, with the help of JGvdB, MS, and KBT. PH, MS, and JGvdB wrote the manuscript, with input from all authors. All authors have read, contributed to and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWilkerson RC, Linton YM \u0026amp; Strickman D. Mosquitoes of the world. Vols. 1 and 2. Baltimore: Johns Hopkins University Press; 2021. ISBN 978-1-421438-14-6.\u003c/li\u003e\n\u003cli\u003eMedlock JM, Hansford KM, Schaffner F, Versteirt V, Hendrickx G, Zeller H et al. A review of the invasive mosquitoes in Europe: ecology, public health risks, and control options. Vector Borne Zoonotic Dis. 2012;12(6):435\u0026ndash;447. DOI: 10.1089/vbz.2011.0814\u003c/li\u003e\n\u003cli\u003ePetrić D, Bellini R, Scholte EJ, Rakotoarivony LM \u0026amp; Schaffner F. Monitoring population and environmental parameters of invasive mosquito species in Europe. Parasit Vectors. 2014;7(187). DOI: 10.1186/1756-3305-7-187\u003c/li\u003e\n\u003cli\u003eElbers ARW, Koenraadt CJM \u0026amp; Meiswinkel R. Mosquitoes and \u003cem\u003eCulicoides\u003c/em\u003e biting midges: vector range and the influence of climate change. Rev Sci Tech Off Int Epiz. 2015;34(1):123\u0026ndash;137. DOI: 10.20506/rst.34.1.2349\u003c/li\u003e\n\u003cli\u003eMwingira V, Mboera LEG, Dicke M \u0026amp; Takken W. Exploiting the chemical ecology of mosquito oviposition behavior in mosquito surveillance and control: a review. J Vector Ecol. 2020;45(2):155\u0026ndash;179. DOI: 10.1111/jvec.12387\u003c/li\u003e\n\u003cli\u003eRenault D, Derocles SAP, Haubrock P, Simard F, Cuthbert RN \u0026amp; Valiente-Moro C. Biological, ecological and trophic features of invasive mosquitoes and other hematophagous arthropods: what makes them successful? Biol Invasions. 2024;26:33\u0026ndash;55. DOI: 10.1007/s10530-023-03158-5\u003c/li\u003e\n\u003cli\u003eFonseca DM, Widdel AK, Hutchinson M, Spichiger SE \u0026amp; Kramer LD. Fine-scale spatial and temporal population genetics of \u003cem\u003eAedes japonicus\u003c/em\u003e, a new US mosquito, reveal multiple introductions. Mol Ecol. 2010;19:1559\u0026ndash;1572. DOI: 10.1111/j.1365-294X.2010.04576.x\u003c/li\u003e\n\u003cli\u003eUrdaneta-Marquez L \u0026amp; Failloux AB. Population genetic structure of \u003cem\u003eAedes aegypti\u003c/em\u003e, the principal vector of dengue viruses. Infect Genet Evol. 2011;11:253\u0026ndash;261. DOI: 10.1016/j.meegid.2010.11.020\u003c/li\u003e\n\u003cli\u003eJanssen N, Werner D \u0026amp; Kampen H. Population genetics of the invasive Asian bush mosquito \u003cem\u003eAedes japonicus\u003c/em\u003e (Diptera, Culicidae) in Germany\u0026ndash;a re-evaluation in a time period of separate populations merging. Parasitol Res. 2019;118:2475\u0026ndash;2484. DOI: 10.1007/s00436-019-06376-w\u003c/li\u003e\n\u003cli\u003eLi SP, Jiang F, Lu H, Kang X, Wang YH, Zou Z et al. Mosquito diversity and population genetic structure of six mosquito species from Hainan Island. Front Genet. 2020;11:602863. DOI: 10.3389/fgene.2020.602863\u003c/li\u003e\n\u003cli\u003eChoi KS, Koekemoer LL \u0026amp; Coetzee M. Population genetic structure of the major malaria vector \u003cem\u003eAnopheles funestus s.s.\u003c/em\u003e and allied species in southern Africa. Parasit Vectors. 2012;5:283. DOI: 10.1186/1756-3305-5-283\u003c/li\u003e\n\u003cli\u003eSunil S, Singh OP, Nanda N, Raghavendra K, Niranjan Reddy BP \u0026amp; Subbarao SK. Analysis of population genetic structure of Indian \u003cem\u003eAnopheles culicifacies\u003c/em\u003e species A using microsatellite markers. Parasit Vectors. 2013;6:166. DOI: 10.1186/1756-3305-6-166\u003c/li\u003e\n\u003cli\u003eWilke ABB, Oliveira Vidal P, Suesdek L \u0026amp; Toledo Marrelli M. Population genetics of neotropical \u003cem\u003eCulex quinquefasciatus\u003c/em\u003e (Diptera: Culicidae). Parasit Vectors. 2014;7:468. DOI: 10.1186/s13071-014-0468-8\u003c/li\u003e\n\u003cli\u003eBunmee K, Thaenkham U, Saralamba N, Ponlawat A, Zhong DB, Cui LW et al. Population genetic structure of the malaria vector \u003cem\u003eAnopheles minimus\u003c/em\u003e in Thailand based on mitochondrial DNA markers. Parasit Vectors. 2021;14:496. DOI: 10.1186/s13071-021-04998-7\u003c/li\u003e\n\u003cli\u003eGao J, Zhang HD, Guo XX, Xing D, Dong YD, Lan CJ et al. Dispersal patterns and population genetic structure of \u003cem\u003eAedes albopictus\u003c/em\u003e (Diptera: Culicidae) in three different climatic regions of China. Parasit Vectors. 2021;14:12. DOI: 10.1186/s13071-020-04521-4\u003c/li\u003e\n\u003cli\u003eShin J \u0026amp; Jung J. Comparative population genetics of the invasive mosquito \u003cem\u003eAedes albopictus\u003c/em\u003e and the native mosquito \u003cem\u003eAedes flavopictus\u003c/em\u003e in the Korean peninsula. Parasit Vectors. 2021;14:377. DOI: 10.1186/s13071-021-04873-5\u003c/li\u003e\n\u003cli\u003eFonseca DM, Smith JL, Wilkerson RC \u0026amp; Fleischer RC. Pathways of expansion and multiple introductions illustrated by large genetic differentiation among worldwide populations of the southern house mosquito. Am J Trop Med Hyg. 2006;74(2):284\u0026ndash;289.\u003c/li\u003e\n\u003cli\u003eSzalanski AL, Owens CB, Lewter JA \u0026amp; Broce AB. Genetic structure of \u003cem\u003eAedes vexans\u003c/em\u003e (Diptera: Culicidae) populations from central United States based on mitochondrial ND5 sequences. Ann Entomol Soc Am. 2006;99(1):157\u0026ndash;163. DOI: 10.1603/0013-8746(2006)099[0157:GSOAVD]2.0.CO;2\u003c/li\u003e\n\u003cli\u003eHasan AU, Suguri S, Ahmed SMU, Fujimoto C, Harada M, Rahman SM et al. Molecular phylogeography of \u003cem\u003eCulex quinquefasciatus\u003c/em\u003e mosquitoes in central Bangladesh. Acta Trop. 2009;112:106\u0026ndash;114. DOI: 10.1016/j.actatropica.2009.07.005\u003c/li\u003e\n\u003cli\u003eMorais SA, de Almeida F, Suesdek L \u0026amp; Marrelli MT. Low genetic diversity in \u003cem\u003eWolbachia\u003c/em\u003e-infected \u003cem\u003eCulex quinquefasciatus\u003c/em\u003e (Diptera: Culicidae) from Brazil and Argentina. Rev Inst Med Trop Sao Paulo. 2012;54(6):325\u0026ndash;329.\u003c/li\u003e\n\u003cli\u003eLow VL, Lim PE, Chen CD, Lim YAL, Tan TK, Norma-Rashid Y et al. Mitochondrial DNA analyses reveal low genetic diversity in \u003cem\u003eCulex quinquefasciatus\u003c/em\u003e from residential areas in Malaysia. Med Vet Entomol. 2014;28:157\u0026ndash;168. DOI: 10.1111/mve.12022\u003c/li\u003e\n\u003cli\u003eSherpa S, Rioux D, Goindin D, Fouque F, Fran\u0026ccedil;ois O \u0026amp; Despr\u0026eacute;s L. At the origin of a worldwide invasion: unraveling the genetic makeup of the Caribbean bridgehead populations of the dengue vector \u003cem\u003eAedes aegypti\u003c/em\u003e. Genome Biol Evol. 2017;10(1):56\u0026ndash;71. DOI: 10.1093/gbe/evx267\u003c/li\u003e\n\u003cli\u003eSherpa S, Rioux D, Pougnet-Lagarde C \u0026amp; Despr\u0026eacute;s L. Genetic diversity and distribution differ between long-established and recently introduced populations in the invasive mosquito \u003cem\u003eAedes albopictus\u003c/em\u003e. Infect Genet Evol. 2018;58:145\u0026ndash;156. DOI: 10.1016/j.meegid.2017.12.018\u003c/li\u003e\n\u003cli\u003eHasan AU, Suguri S, Fujimoto C, Itaki RL, Harada M, Kawabata M et al. Genetic diversity in two sibling species of the \u003cem\u003eAnopheles punctulatus\u003c/em\u003e group of mosquitoes on Guadalcanal in the Solomon Islands. BMC Evol Biol. 2008;8:318. DOI: 10.1186/1471-2148-8-318\u003c/li\u003e\n\u003cli\u003eBataille A, Cunningham AA, Cede\u0026ntilde;o V, Pati\u0026ntilde;o L, Constantinou A, Kramer LD et al. Natural colonization and adaptation of a mosquito species in Gal\u0026aacute;pagos and its implications for disease threats to endemic wildlife. Proc Natl Acad Sci U S A. 2009;106(25):10230\u0026ndash;10235. DOI: 10.1073/pnas.0901308106\u003c/li\u003e\n\u003cli\u003ePanda D \u0026amp; Barik TK. Molecular characterization and genetic divergence of seven \u003cem\u003eCulex\u003c/em\u003e mosquito (Diptera: Culicidae) species using Mt COI gene from Odisha state, India. J Basic Appl Zool. 2022;83:41. DOI: 10.1186/s41936-022-00305-7\u003c/li\u003e\n\u003cli\u003eService MW. Mosquito (Diptera: Culicidae) dispersal: the long and short of it. J Med Entomol. 1997;34(6):579\u0026ndash;588.\u003c/li\u003e\n\u003cli\u003eVerdonschot PFM \u0026amp; Besse-Lototskaya AA. Flight distance of mosquitoes (Culicidae): a metadata analysis to support the management of barrier zones around rewetted and newly constructed wetlands. Limnologica. 2014;45:69\u0026ndash;79. DOI: 10.1016/j.limno.2013.11.002\u003c/li\u003e\n\u003cli\u003eDebrot AO, Henkens RJHG \u0026amp; Verweij PJFM. Staat van de natuur van Caribisch Nederland 2017: een eerste beoordeling van de staat (van instandhouding), bedreigingen en managementimplicaties van habitats en soorten in Caribisch Nederland. Rapport Co86/17. Wageningen: Wageningen Marine Research; 2018.\u003c/li\u003e\n\u003cli\u003eVan der Kuyp E. Mosquitoes of the Netherlands Antilles and their hygienic importance. Stud. Fauna Cura\u0026ccedil;ao. 1954;5:37\u0026ndash;114.\u003c/li\u003e\n\u003cli\u003eMartinez C, Goddard L, Kushnir Y \u0026amp; Ting MF. Seasonal climatology and dynamical mechanisms of rainfall in the Caribbean. Clim Dynam. 2019;53:825\u0026ndash;846. DOI: 10.1007/s00382-019-04616-4\u003c/li\u003e\n\u003cli\u003eKNMI: hour data Caribbean area; 2023. https://www.knmi.nl/nederland-nu/klimatologie/uurgegevens_Caribisch_gebied. Accessed 12 Oct 2023.\u003c/li\u003e\n\u003cli\u003eNU.CW; 2022. https://nu.cw/2022/11/03/nog-meer-regen-voor-de-abc-eilanden/. Accessed 15 Nov 2022.\u003c/li\u003e\n\u003cli\u003eJohnston E, Weinstein P, Slaney D, Flies AS, Fricker S \u0026amp; Williams C. Mosquito communities with trap height and urban-rural gradient in Adelaide, South Australia: implications for disease vector surveillance. J Vector Ecol. 2014;39(1):48\u0026ndash;55. DOI: 10.1111/j.1948-7134.2014.12069.x\u003c/li\u003e\n\u003cli\u003eEuropean Centre for Disease Prevention and Control; European Food Safety Authority. Field sampling methods for mosquitoes, sandflies, biting midges and ticks: VectorNet project 2014\u0026ndash;2018. Stockholm and Parma: ECDC and EFSA; 2018.\u003c/li\u003e\n\u003cli\u003eLane J. Neotropical Culicidae. Vol. I and II. S\u0026atilde;o Paulo: University of S\u0026atilde;o Paulo; 1953.\u003c/li\u003e\n\u003cli\u003ePratt HD. Key to the Culicidae of Puerto Rico. 1969.\u003c/li\u003e\n\u003cli\u003eBelkin JN, Heinemann SJ \u0026amp; Page WA. The Culicidae of Jamaica (Mosquito Studies. XXI). Contrib Am Entomol Inst. 1970;6:1\u0026ndash;458.\u003c/li\u003e\n\u003cli\u003eDarsie RF, Scott Taylor D, Prusak ZA \u0026amp; Verna TN. Checklist of the mosquitoes of the Bahamas with three additions to its fauna and keys to the adult females and fourth instars. J Am Mosq Control Assoc. 2010;26(2):127\u0026ndash;134. DOI: 10.2987/09-5982.1\u003c/li\u003e\n\u003cli\u003eBurkett-Cadena ND. Mosquitoes of the Southeastern United States. Tuscaloosa: The University of Alabama Press; 2013.\u003c/li\u003e\n\u003cli\u003eVan der Beek JG, Dijkstra KDB, Van der Hoorn BB, Boerlijst SP, Busscher L, Kok ML et al. Taxonomy, ecology and distribution of the mosquitoes (Diptera: Culicidae) of the Dutch Leeward Islands, with a key to the adults and fourth instar larvae. Contrib Zool. 2020;89:373\u0026ndash;392. DOI: 10.1163/18759866-bja10005\u003c/li\u003e\n\u003cli\u003eArnell JH. Mosquito studies (Diptera, Culicidae) XXXII: a revision of the genus \u003cem\u003eHaemagogus\u003c/em\u003e. Contrib Am Entomol Inst. 1973;10(2):1\u0026ndash;174.\u003c/li\u003e\n\u003cli\u003eBelkin JN. The mosquitoes of the South Pacific (Diptera: Culicidae). Vols. 1 and 2. California: University of California Press; 1962.\u003c/li\u003e\n\u003cli\u003ePowell JR \u0026amp; Tabachnick WJ. History of domestication and spread of \u003cem\u003eAedes aegypti\u003c/em\u003e: a review. Mem Inst Oswaldo Cruz. 2013;108(1):11\u0026ndash;17. DOI: 10.1590/0074-0276130395\u003c/li\u003e\n\u003cli\u003eOshaghi MA. mtDNA inheritance in the mosquitoes of \u003cem\u003eAnopheles stephensii\u003c/em\u003e. Mitochondrion. 2005;5:266\u0026ndash;271. DOI: 10.1016/j.mito.2005.05.001\u003c/li\u003e\n\u003cli\u003eMoore WS. Inferring phylogenies from mtDNA variation: mitochondrial-gene trees versus nuclear-gene trees. Evolution. 1995;49(4):718\u0026ndash;726.\u003c/li\u003e\n\u003cli\u003eRubinoff D, Cameron S \u0026amp; Will K. A genomic perspective on the shortcomings of mitochondrial DNA for \u0026ldquo;barcoding\u0026rdquo; identification. J Hered. 2006;97(6):581\u0026ndash;594. DOI: 10.1093/jhered/esl036\u003c/li\u003e\n\u003cli\u003eZink RM \u0026amp; Barrowclough GF. Mitochondrial DNA under siege in avian phylogeography. Mol Ecol. 2008;17:2107\u0026ndash;2121. DOI: 10.1111/j.1365-294X.2008.03737.x\u003c/li\u003e\n\u003cli\u003eTrimbos KB, Doorenweerd C, Kraaijeveld K, Musters CJM, Groen NM, de Knijff P et al. Patterns in nuclear and mitochondrial DNA reveal historical and recent isolation in the Black-Tailed Godwit (\u003cem\u003eLimosa limosa\u003c/em\u003e). PLoS One. 2014;9(1):e83949. DOI: 10.1371/journal.pone.0083949\u003c/li\u003e\n\u003cli\u003eChan A, Chiang LP, Hapuarachchi HC, Tan CH, Pang SC, Lee R et al. DNA barcoding: complementing morphological identification of mosquito species in Singapore. Parasit Vectors. 2014;7(569). DOI: 10.1186/s13071-014-0569-4\u003c/li\u003e\n\u003cli\u003eHern\u0026aacute;ndez-Triana LM, Brugman VA, Pramual P, Barrero E, Nikilova NI, Ruiz-Arrondo I et al. Genetic diversity and population structure of \u003cem\u003eCulex modestus\u003c/em\u003e across Europe: does recent appearance in the United Kingdom reveal a tendency for geographical spread? Med Vet Entomol. 2014. DOI: 10.1111/mve.12412.\u003c/li\u003e\n\u003cli\u003eLe Goff G, Bouss\u0026egrave;s P, Julienne S, Brengues C, Rahola N, Rocamora G et al. The mosquitoes (Diptera: Culicidae) of Seychelles: taxonomy, ecology, vectorial importance, and identification keys. Parasit Vectors. 2012;5(207). DOI: 10.1186/1756-3305-5-207\u003c/li\u003e\n\u003cli\u003eKnobloch EC \u0026amp; Schmidt RC: Non-destructively barcoding hundreds of freshwater macroinvertebrates with a MinION; 2022. https://www.protocols.io/view/non-destructively-barcoding-hundreds-of-freshwater-cbh6sj9e.html. Accessed 1 Jan 2023.\u003c/li\u003e\n\u003cli\u003eBergsten J, Brilmyer G, Crampton-Platt A \u0026amp; Nilsson AN. Sympatry and colour variation disguised well-differentiated sister species: \u003cem\u003eSuphrodytes\u003c/em\u003e revised with integrative taxonomy including 5 kbp of housekeeping genes (Coleoptera: Dytiscidae). DNA Barcodes. 2012;1:1\u0026ndash;18. DOI: 10.2478/dna-2012-0001\u003c/li\u003e\n\u003cli\u003eCristiano MP, Fernandes-Salom\u0026atilde;o TM \u0026amp; Yotoko KSC. Nuclear mitochondrial DNA: an Achilles\u0026rsquo; heel of molecular systematics, phylogenetics, and phylogeographic studies of stingless bees. Apidologie. 2012;43:527\u0026ndash;538. DOI: 10.1007/s13592-012-0122-4\u003c/li\u003e\n\u003cli\u003eWang YH, Zhao Y, Bollas A, Wang Y \u0026amp; Au KF. Nanopore sequencing technology, bioinformatics and applications. Nat Biotechnol. 2021;39:1348\u0026ndash;1365. DOI: 10.1038/s41587-021-01108-x\u003c/li\u003e\n\u003cli\u003eOkonechnikov K, Golosova O, Fursov M, the UGENE team. Unipro UGENE: a unified bioinformatics toolkit. Bioinformatics. 2012;28:1166\u0026ndash;1167. DOI:10.1093/bioinformatics/bts091\u003c/li\u003e\n\u003cli\u003eEdgar RC. MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics. 2004;5:113. DOI: 10.1186/1471-2105-5-113\u003c/li\u003e\n\u003cli\u003eLeigh JW, Bryant D \u0026amp; Steel M. popart documentation: Data Input. Otago, University of Otago; 2023. https://popart.maths.otago.ac.nz/documentation/. Accessed 12 May 2023.\u003c/li\u003e\n\u003cli\u003eBOLD. BOLD: The Barcode of Life Data System. Mol Ecol Notes. 2007. www.boldsystems.org\u003c/li\u003e\n\u003cli\u003eLeigh JW \u0026amp; Bryant D. popart: full-feature software for haplotype network construction. Methods Ecol Evol. 2015;6:1110\u0026ndash;1116. https://popart.maths.otago.ac.nz/ DOI: 10.1111/2041-210X.12410\u003c/li\u003e\n\u003cli\u003eBandelt H, Forster P \u0026amp; R\u0026ouml;hl A. Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol. 1999;16(1):37\u0026ndash;38.\u003c/li\u003e\n\u003cli\u003eClement M, Snell Q, Walke P, Posada D \u0026amp; Crandall K. TCS: estimating gene genealogies. Proc 16 IPDPS. 2002;2:184.\u003c/li\u003e\n\u003cli\u003eRozas J, Ferrer-Mata A, S\u0026aacute;nchez-DelBarrio JC, Guirao-Rico S, Librado P, Ramos-Onsins SE et al. DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol Biol Evol. 2017;34(12):3299\u0026ndash;3302. DOI: 10.1093/molbev/msx248\u003c/li\u003e\n\u003cli\u003eTajima F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics. 1989;123:585\u0026ndash;595.\u003c/li\u003e\n\u003cli\u003eFu YX. Statistical tests of neutrality of mutations against population growth, hitchhiking and background selection. Genetics. 1997;147:915\u0026ndash;925.\u003c/li\u003e\n\u003cli\u003eSharma M, Fomda BA, Mazta S, Sehgal R, Singh BB \u0026amp; Malla N. Genetic diversity and population genetic structure analysis of \u003cem\u003eEchinococcus granulosus sensu stricto\u003c/em\u003e complex based on mitochondrial DNA signature. PLoS One. 2013;8(12):e82904. DOI: 10.1371/journal.pone.0082904\u003c/li\u003e\n\u003cli\u003eMinh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD, von Haeseler A et al. IQ-Tree 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol Biol Evol. 2020;37(5):1530\u0026ndash;1534. DOI: 10.1093/molbev/msaa015\u003c/li\u003e\n\u003cli\u003eKalyaanamoorthy S, Minh BQ, Wong TFK, von Haeseler A \u0026amp; Jermiin LS. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat Methods. 2017;14(6):587\u0026ndash;589. DOI: 10.1038/nmeth.4285\u003c/li\u003e\n\u003cli\u003eHoang DT, Chernomor O, von Haeseler A, Minh BQ \u0026amp; Vinh LS. UFBoot2: improving the ultrafast bootstrap approximation. Mol Biol Evol. 2017;35(2):518\u0026ndash;522. DOI: 10.1093/molbev/msx281\u003c/li\u003e\n\u003cli\u003eYu GC, Smith DK, Zhu HC, Guan Y \u0026amp; Lam TTY. ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods Ecol Evol\u003cem\u003e.\u003c/em\u003e 2017;8:28\u0026ndash;36. DOI: 10.1111/2041-210x.12628\u003c/li\u003e\n\u003cli\u003eRevell LJ. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol Evol. 2012;3:217\u0026ndash;223. DOI: 10.1111/j.2041-210X.2011.00169.x\u003c/li\u003e\n\u003cli\u003eGloria-Soria A, Ayala D, Bheecarry A, Calderon-Arguedas O, Chadee DD, Chiappero M et al. Global genetic diversity of \u003cem\u003eAedes aegypti\u003c/em\u003e. Mol Ecol. 2016;25:5377\u0026ndash;5395. DOI: 10.1111/mec.13866\u003c/li\u003e\n\u003cli\u003eValdivalagan C, Karthika P, Murugan K, Panneerselvam C, Del Serrone P \u0026amp; Benelli G. Exploring genetic variation in haplotypes of the filariasis vector \u003cem\u003eCulex quinquefasciatus\u003c/em\u003e (Diptera: Culicidae) through DNA barcoding. Acta Trop. 2017;169:43\u0026ndash;50. DOI: 10.1016/j.actatropica.2017.01.020\u003c/li\u003e\n\u003cli\u003eBirader K. Genetic Diversity and the Adaptation of Species to Changing Environments. J Biodivers Endanger Species. 2023;11:474.\u003c/li\u003e\n\u003cli\u003eProvost MW. The dispersal of \u003cem\u003eAedes taeniorhynchus\u003c/em\u003e. 1. Preliminary studies. Mosq News. 1952;12(3):174\u0026ndash;190.\u003c/li\u003e\n\u003cli\u003eHorsfall RB. Mosquitoes: their bionomics and relation to disease. New York: The Ronald Press Company; 1955.\u003c/li\u003e\n\u003cli\u003eBecker N, Petrić D, Zgomba M, Boase C, Madon MB, Dahl C et al. Biology of mosquitoes. In: Mosquitoes. Fascinating Life Sciences, pp 11\u0026ndash;27. Cham: Springer Nature; 2020. DOI: 10.1007/978-3-030-11623-1_2\u003c/li\u003e\n\u003cli\u003eLaurance WF. Beyond island biogeography theory: understanding habitat fragmentation in the real. In: The Theory of Island Biogeography Revisited, edited by Losos JB and Ricklefs RE, pp. 214\u0026ndash;236. Princeton: Princeton University Press; 2010. DOI: 10.1515/9781400831920.214\u003c/li\u003e\n\u003cli\u003eLiu H \u0026amp; Beckenbach AT. Evolution of the mitochondrial cytochrome oxidase II gene among 10 orders of insects. Mol Phylogenet Evol. 1992;1:41\u0026ndash;52. DOI: 10.1016/1055-7903(92)90034-e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e List of primer sets used per species with primer details.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"633\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003ePrimer set (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003ePrimer sequence (5\u0026rsquo;-3\u0026rsquo;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cem\u003eT\u003c/em\u003e\u003csub\u003ea\u003c/sub\u003e (\u0026deg;C)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cem\u003eAe. aegypti\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003eF: SCTL2-J-3037 [80]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003eATGGCAGATTAGTGCAATGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003eR: Ae-COII-R [25]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003eGATTTAAGAGATCATTACTTGC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cem\u003eAe. taeniorhynchus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003eF: SCTL2-J-3037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003eATGGCAGATTAGTGCAATGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003eR: Ae-COII-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003eGATTTAAGAGATCATTACTTGC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cem\u003eCx. nigripalpus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003eF: SCTL2-J-3037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003eATGGCAGATTAGTGCAATGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003eR: Cul-COII-R (\u0026dagger;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003eGRTTTAAGAGAYCAKTACTTGC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cem\u003eCx. quinquefasciatus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003eF: SCTL2-J-3037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003eATGGCAGATTAGTGCAATGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003eR: TK-N-3785 [80]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003eGTTTAAGAGACCAGTACTTG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cem\u003eDeinocerites\u003c/em\u003e sp.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003eF: SCTL2-J-3037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003eATGGCAGATTAGTGCAATGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003eR: Cul-COII-R (\u0026dagger;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003eGRTTTAAGAGAYCAKTACTTGC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cem\u003eHg. chrysochlorus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003eF: SCTL2-J-3037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003eATGGCAGATTAGTGCAATGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003eR: Cul-COII-R (\u0026dagger;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 254px;\"\u003e\n \u003cp\u003eGRTTTAAGAGAYCAKTACTTGC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e(\u0026dagger;) Newly developed reverse primer for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Total numbers of specimens per island and per species included in the present study. Note that the total number of locations is not equal to the sum of either the number of locations per species or the number of locations per island, since a number of specimens from different species were sampled at the same location, for example in a BG Pro Trap.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"661\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003en\u003csub\u003eAruba\u003c/sub\u003e\u003c/em\u003e (\u003cem\u003en\u003csub\u003elocations\u003c/sub\u003e\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cem\u003en\u003csub\u003eCura\u0026ccedil;ao\u003c/sub\u003e\u003c/em\u003e (\u003cem\u003en\u003csub\u003elocations\u003c/sub\u003e\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cem\u003en\u003csub\u003eBonaire\u003c/sub\u003e\u003c/em\u003e (\u003cem\u003en\u003csub\u003elocations\u003c/sub\u003e\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cem\u003en\u003csub\u003etotal\u003c/sub\u003e\u003c/em\u003e (\u003cem\u003en\u003csub\u003elocations\u003c/sub\u003e\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eAe. aegypti\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp; 6 (\u003cem\u003e4\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp; 7 (\u003cem\u003e4\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp; 7 (\u003cem\u003e4\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e20 (\u003cem\u003e12\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eAe. taeniorhynchus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e12 (\u003cem\u003e7\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e13 (\u003cem\u003e7\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e13 (\u003cem\u003e7\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e38 (\u003cem\u003e21\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eCx. nigripalpus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e21 (\u003cem\u003e8\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e18 (\u003cem\u003e7\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e19 (\u003cem\u003e6\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e58 (\u003cem\u003e21\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eCx. quinquefasciatus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e21 (\u003cem\u003e12\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e17 (\u003cem\u003e9\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e14 (\u003cem\u003e8\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e52 (\u003cem\u003e29\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eDeinocerites\u003c/em\u003e sp.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e23 (\u003cem\u003e7\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e16 (\u003cem\u003e4\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e15 (\u003cem\u003e4\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e54 (\u003cem\u003e15\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eHg. chrysochlorus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp; 2 (\u003cem\u003e1\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e13 (\u003cem\u003e8\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e21 (\u003cem\u003e13\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e36 (\u003cem\u003e22\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e85 (\u003cem\u003e39\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e84 (\u003cem\u003e39\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e89 (\u003cem\u003e42\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e258 (\u003cem\u003e108\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e Summary of the population genetic statistics of the mitochondrial \u003cem\u003eCOII\u003c/em\u003e sequences for all six studied species. For each species: the number of sequences included in the calculation (\u003cem\u003eCOII\u003c/em\u003e), the number of haplotypes (\u003cem\u003eH\u003c/em\u003e), the number of segregating or polymorphic sites (\u003cem\u003eS\u003c/em\u003e), the nucleotide diversity (\u003cem\u003e\u0026pi;\u003c/em\u003e), the haplotype diversity (\u003cem\u003eHd\u003c/em\u003e), the standard error of the haplotype diversity (\u003cem\u003es (Hd)\u003c/em\u003e), estimated Tajima\u0026rsquo;s \u003cem\u003eD\u003c/em\u003e (\u003cem\u003eD\u003c/em\u003e), the p-value for the estimated Tajima\u0026rsquo;s \u003cem\u003eD\u003c/em\u003e (\u003cem\u003eP (D)\u003c/em\u003e), and estimated Fu\u0026rsquo;s \u003cem\u003eF\u003csub\u003eS\u003c/sub\u003e\u003c/em\u003e (\u003cem\u003eF\u003csub\u003eS\u003c/sub\u003e\u003c/em\u003e). Significance shown as *\u003cem\u003eP\u003c/em\u003e\u0026lt;0.5 or NS (not significant).\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003eCOII\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cem\u003eH\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cem\u003eS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026pi;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003eHd\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003es (Hd)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cem\u003eD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003eP (D)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003csub\u003eS\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eAe. aegypti\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.00296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.31665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e3.244\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eCx. quinquefasciatus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.00028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-1.98592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-6.970\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eCx. nigripalpus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.00644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-1.04344\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-16.792\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eAe. taeniorhynchus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.00612\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.826\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-0.67506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-3.188\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eDeinocerites\u003c/em\u003e sp.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.00606\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.885\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.15591\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-2.636\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eHg. chrysochlorus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.00320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.803\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-1.92392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-13.105\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"parasites-and-vectors","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"parv","sideBox":"Learn more about [Parasites \u0026 Vectors](http://parasitesandvectors.biomedcentral.com/)","snPcode":"13071","submissionUrl":"https://submission.nature.com/new-submission/13071/3","title":"Parasites \u0026 Vectors","twitterHandle":"@bugbittentweets","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Mosquitoes, Genetic diversity, Population structure, Haplotype network, Dispersal, Mitochondrial DNA, Introduced species, Dutch Caribbean.","lastPublishedDoi":"10.21203/rs.3.rs-5250794/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5250794/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eDespite their medical and veterinary importance, little is known about the general patterns in genetic population structure of mosquitoes. The scarce information that is available comes from a small subsample of cosmopolitan (and often pathogen-transmitting) species. This greatly hampers our ability to generalise previously described patterns of variation in mosquito population genetics to global mosquito biodiversity. This study aimed to explore variation in population genetics of species from a wide range of ecological niches and how variation in these patterns relates to species-specific ecologies and population history, using the mosquito fauna of the Caribbean islands of Aruba, Curaçao, and Bonaire as a case study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Mitochondrial \u003cem\u003eCOII\u003c/em\u003e sequences were obtained from 258 mosquito specimens belonging to six species, occurring on all three islands. Sequences were used in phylogenetic analysis and haplotype network analysis to assess the genetic variation between mosquito populations of each of the six ecologically diverse species, which vary in both their population history and ecological niche.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Both the genetic diversity and population genetic structure were found to differ strongly between sets of species, leading to a subdivision into three species groups: i) non-native species with low genetic diversity across all three investigated islands; ii) locally native species with high genetic diversity and closely related haplotypes occurring on different islands; iii) locally native species with high genetic diversity and locally restricted haplotypes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Our results show that the population genetics of non-native and native species strongly differ, likely as a result of population history. Furthermore, the results suggest that native populations may display distinct population genetic structure, which is likely related to differences in their ecology and dispersal capacity. Based on these results, we hypothesize that similar contrasts in mosquito population genetics along historical and ecological axes may be present worldwide.\u003c/p\u003e","manuscriptTitle":"The ecological niche and population history shape mosquito population genetics: a case study from Caribbean islands","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-25 15:28:58","doi":"10.21203/rs.3.rs-5250794/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-02T16:44:29+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-26T20:51:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-12T17:51:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"124453839722440898378164025598242264740","date":"2024-10-25T04:43:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"89782255952664257347685112551977943025","date":"2024-10-24T18:25:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"217629628119311349154518613558356913215","date":"2024-10-24T12:43:06+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-10-22T08:34:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-15T12:49:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-10-15T12:32:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Parasites \u0026 Vectors","date":"2024-10-12T09:46:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"parasites-and-vectors","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"parv","sideBox":"Learn more about [Parasites \u0026 Vectors](http://parasitesandvectors.biomedcentral.com/)","snPcode":"13071","submissionUrl":"https://submission.nature.com/new-submission/13071/3","title":"Parasites \u0026 Vectors","twitterHandle":"@bugbittentweets","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8c256873-5ee5-4ec0-8427-d3719d7c7685","owner":[],"postedDate":"December 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-12T15:59:24+00:00","versionOfRecord":{"articleIdentity":"rs-5250794","link":"https://doi.org/10.1186/s13071-025-06801-3","journal":{"identity":"parasites-and-vectors","isVorOnly":false,"title":"Parasites \u0026 Vectors"},"publishedOn":"2025-05-09 15:57:04","publishedOnDateReadable":"May 9th, 2025"},"versionCreatedAt":"2024-12-25 15:28:58","video":"","vorDoi":"10.1186/s13071-025-06801-3","vorDoiUrl":"https://doi.org/10.1186/s13071-025-06801-3","workflowStages":[]},"version":"v1","identity":"rs-5250794","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5250794","identity":"rs-5250794","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}