The co-existence patterns between native and an invasive mosquito species in Hungary based on a field survey

165 The co-existence patterns between native and an invasive mosquito species in Hungary based on a field survey Zoltán Soltész1,2 , Zoltán Kenyeres3, Gábor Markó4, Gergely Nagy1, László Zsolt Garamszegi1,2 1 Institute of Ecology and Botany, HUN-REN Centre for Ecological Research, Vácrátót, Hungary 2 National Laboratory for Health Security, HUN-REN Centre for Ecological Research, Budapest, Hungary 3 Acrida Conservational Research L.P., Tapolca, Hungary 4 Hungarian University of Agriculture and Life Sciences, Institute of Plant Protection, Department of Plant Pathology, Budapest, Hungary Corresponding author: Zoltán Soltész ([email protected]) Copyright: © Zoltán Soltész et al. This is an open access article distributed under terms of the Creative Commons Attribution License (Attribution 4.0 International – CC BY 4.0). Research Article Abstract Biological invasions by non-native mosquito species pose significant global economic and public health threats due to their high vector competence. Still, their ecological relationships with the native fauna are rarely considered. This field study investigates the association between Aedes albopictus and the native mosquito community in Hungary. We conducted field sampling from 2020 to 2023, identified 104,612 mosquitoes from 29 species captured in traps across 532 locations, and characterized species diversity as well as the abundance of native species at each trapping event. We found that, where Ae. albopictus is already present, its abundance was positively associated with the species richness and diversity of native mosquitoes even after controlling for spatial and seasonal effects. We identified several significant pair-wise associations between Ae. albopictus and native species, both in positive and negative directions. These correlative patterns may indicate either direct interaction between species (e.g., competition) or patterns of co-existence that are driven by a third variable in the background. We performed path analyses to uncover the causal relationship among environmental traits (temperature, precipitation, urbanization and distance from water surfaces), the abundance of Ae. albopictus and that of four native species depicting co-existence patterns with the invasive one. These analyses revealed that the co-occurrences of Ae. albopictus with Anopheles plumbeus and Coquillettidia richiardii were mediated by seasonal activity, indicating that invasive mosquitoes can thrive in ecological conditions that disfavor native species. However, path models for Ochlerotatus dorsalis and Oc. geniculatus suggested a more direct causal relationship with Ae. albopictus. Although we cannot exclude that interspecific competition may partly shape the distribution of invasive and native mosquitoes, environmental filtering via shared ecological preferences appears to play a dominant role in structuring co-occurrence patterns. Key words: Aedes albopictus, BG-Sentinel mosquito trap, competitive exclusion, ecological niche, emerging infectious diseases Introduction Biological invasion refers to the process by which non-native species spread into new environments and establish populations, and often has significant ecological, economic, and social impacts (Simberloff et al. 2013). Human activities, such as trade and travel, play an important role in introducing and spreading non-native species worldwide. Invasive species significantly alter ecological interactions by Academic editor: Ross Cuthbert Received: 18 July 2025 Accepted: 29 September 2025 Published: 24 October 2025 Citation: Soltész Z, Kenyeres Z, Markó G, Nagy G, Garamszegi LZ (2025) The co-existence patterns between native and an invasive mosquito species in Hungary based on a field survey. NeoBiota 103: 165–185. https://doi. org/10.3897/neobiota.103.165442 NeoBiota 103: 165–185 (2025) DOI: 10.3897/neobiota.103.165442 Advancing research on alien species and biological invasions A peer-reviewed open-access journal NeoBiota 166 NeoBiota 103: 165–185 (2025), DOI: 10.3897/neobiota.103.165442 Zoltán Soltész et al.: Co-existence patterns between invasive and native mosquitoes competing with natives for resources, disrupting food webs, modifying habitats, transmitting diseases, and causing genetic changes through hybridization (McMichael and Bouma 2000; Richardson 2011; Pyšek et al. 2012). Therefore, invasive species exert their influence on other native species and ecosystems primarily through their biotic interactions, which encompass predation, parasitism, interspecific competition, and ecosystem engineering. These impacts can lead to declines in native species, ecosystem instability, and a reduction in ecosystem services crucial for human well-being. Understanding the impact of invasive species is vital to preserve native biodiversity and ecosystem functioning. An increasing number of invasive mosquito species have appeared in Europe, posing substantial and immediate risks to public health and ecosystems, with Aedes albopictus being the most abundant and threatening (Medlock et al. 2015). The establishment and expected drastic expansion of this invasive mosquito in Europe (Carlassara et al. 2024) raises urgent concerns due to their ability to transmit various pathogens, such as viruses causing chikungunya, Zika fever, yellow fever, West Nile fever, Eastern equine encephalitis, La Crosse encephalitis, St. Louis encephalitis, Japanese encephalitis, or Rift Valley fever (Hubálek 2008; Medlock et al. 2012). Mosquito-borne diseases can significantly impact human populations, ranging from mild symptoms to severe illness and even death. Furthermore, the presence of invasive mosquito species could also disrupt local ecosystems and native species interactions, but these ecological impacts are generally less studied than the epidemiological consequences (Juliano and Lounibos 2005). Theories about the ecological interactions of invasive species often emphasize that competition plays a pivotal role in shaping species assemblages, particularly when invasive species exploit similar resources and habitats as native species. One classic outcome of such competition is the competitive exclusion principle, which states that two species competing for the same limiting resources cannot stably coexist in the same ecological niche (Hardin 1960). In such cases, one species typically outcompetes and displaces the other, leading to a negative association between the abundance or presence of the competing species (Juliano and Lounibos 2005). However, coexistence may still emerge when species exhibit niche partitioning, whereby differences in behavior, temporal activity, habitat use, or resource preference reduce the intensity of direct competition (Schoener 1974; Chesson 2000). Niche partitioning allows for overlapping geographic distributions without direct competitive displacement. In relation to invasive mosquitoes, most available studies suggest that these species can occasionally have neutral or even positive effects on native or co-occurring species, while a few works indicate that they play a role in competition. For example, Aedes japonicus may enhance oviposition site attractiveness for Culex pipiens, thereby indirectly facilitating co-occurrence through behavioral cues (Kaufman et al. 2012). Similarly, the presence of multiple larval species, including Ae. albopictus, may dilute predation pressure on native mosquitoes, such as Culex restuans, leading to increased survival in shared habitats (Kesavaraju et al. 2007). In other cases, invasive species may modify the microbial community of breeding sites in ways that influence the growth or habitat selection of other species (Murrell and Juliano 2008). Nevertheless, some studies have demonstrated direct larval competition between invasive and native mosquitoes under controlled conditions (Juliano 1998; Juliano and Lounibos 2005), indicating that such interactions may occur under specific ecological contexts. These examples underscore that community 167 NeoBiota 103: 165–185 (2025), DOI: 10.3897/neobiota.103.165442 Zoltán Soltész et al.: Co-existence patterns between invasive and native mosquitoes dynamics can also include indirect facilitative effects, and that not all outcomes of species introductions are necessarily antagonistic. One of the most common approaches to infer ecological interactions between invasive and native species from field studies is the analysis of correlations in their prevalence or abundance across space and time. These co-occurrence patterns— whether positive or negative—are often used as proxies for making inferences about biotic relationships such as competition, facilitation, or neutral coexistence (Blanchet et al. 2020). However, observed co-occurrence patterns (either positive or negative) between invasive and native species in the field may also reflect shared habitat preferences or environmental filtering rather than biotic interactions. That is, species may co-occur simply because they are independently attracted to similar environmental conditions, such as urban habitats with artificial breeding sites or areas with suitable microclimates (Leibold et al. 2004; Götzenberger et al. 2012). In this context, habitat attraction or environmental affinity could lead to positive species associations, even in the absence of direct ecological interaction. Similarly, if species match their seasonal activity with the same environmental fluctuations, a positive association will exist between the abundance of these species across time (Blonder et al. 2014). On the other hand, a negative association between species’ abundance can emerge in a given location without direct interaction between them if the species favor different ecological conditions. Accordingly, if species are attracted to different environmental optimum, they will be unlikely to be trapped at the same time or at the same location, which will lead to negative co-occurrences. Studies, using field surveillance data, such as trap-based sampling across broad geographic scales, have shown that invasive Aedes albopictus often exhibits negative spatial associations with native species, such as Culex pipiens, Ochlerotatus triseriatus, and Anopheles quadrimaculatus, in parts of North America, suggesting the possibility of competitive exclusion (Benedict et al. 2007; Rochlin et al. 2013). However, other studies have found positive or neutral co-occurrence patterns depending on habitat type and environmental context (Leisnham and Juliano 2010), highlighting the complexity of inferring causality from field data alone. Numerous laboratory and field studies have demonstrated that interspecific competition, particularly among larval stages, could affect or play a significant role in shaping the outcomes of mosquito invasions (Juliano 1998; Braks et al. 2004; Juliano and Lounibos 2005; Kesavaraju et al. 2007). Experimental microcosms and field enclosures have repeatedly shown that the invasive Aedes albopictus is a superior competitor to both the invasive Aedes aegypti and the native North American Ochlerotatus triseriatus, often leading to reduced survival or displacement of the latter under resource-limited conditions (Teng and Apperson 2000). This competitive superiority has been attributed to more efficient resource utilization, insensitivity to inhibitory cues, and, in some cases, asymmetries in mating interference and egg hatching behavior. However, field observations also highlight that coexistence frequently occurs, suggesting condition-specific competition where abiotic factors (e.g., desiccation, temperature) or biotic interactions (e.g., predation, parasite escape) mitigate competitive exclusion. For instance, native predatory mosquitoes, such as Wyeomyia spp. or Toxorhynchites spp., may reduce the establishment success of Ae. albopictus in certain habitats. Overall, while larval competition is a central mechanism in mosquito invasions, its ecological impact is often context-dependent and modulated by broader environmental and community factors (Juliano and Lounibos 2005), while substantial evidence suggests facilitative effects on native species. 168 NeoBiota 103: 165–185 (2025), DOI: 10.3897/neobiota.103.165442 Zoltán Soltész et al.: Co-existence patterns between invasive and native mosquitoes In this study, we investigate the ecological relationships between Ae. albopictus and native mosquito species using a large-scale field dataset collected across Hungary based on samples from adult traps. Ae. albopictus has been introduced in Hungary in the last 15 years (Soltész and Zöldi 2017; Sáringer-Kenyeres et al. 2020), and since then, they depicted a rapid spread (Garamszegi et al. 2023a; www.mosquitosurveillance.hu). We aim to evaluate whether the observed co-occurrence patterns among species are more consistent with direct competitive interaction or environmentally driven aggregation. Negative associations between species may point to competitive exclusion, particularly when species rely on similar larval habitats or resources and their spatial overlap is lower than expected by chance. However, environmentally driven aggregation may emerge if shared environmental preferences or activity patterns generate positive associations, even in the absence of direct biotic interaction. Such environmental mediators can also lead to negative associations between species if they differ in their ecological requirements. To investigate these possibilities, we apply path modeling to our field data collected over four years. The analyses incorporate climatic variables (temperature, precipitation), spatial and seasonal effects, and habitat characteristics (urbanization, proximity to water), allowing us to evaluate the relative contribution of interspecific interactions versus shared environmental responses in shaping mosquito community structure and to test inferences about the causal mechanisms. Materials and methods Direct field sampling We conducted direct field sampling, collecting mosquitoes from 192 settlements and 532 locations during 897 trapping days between 2020 and 2023 (Fig. 1). To ensure national coverage, we selected at least seven settlements randomly from each county using a stratified random sampling method. These short-term traps were operated at each location for a minimum of 24 hours and a maximum of 5 days; however, in most cases, these traps were typically positioned for 2 consecutive nights at a sampling session. We also included 4 long-term traps (Budapest, Debrecen, Vác, Vácrátót) that operated permanently from May to October each year from 2021 and were checked daily. Short-term and long-term traps were purposefully positioned in areas with supposedly high mosquito activity, such as near water bodies and in urban areas. We used a standardized protocol for trap operation and mosquito collection, ensuring the reliability and comparability of our data. BG-Sentinel mosquito traps were used with CO2 and lure as attractants for mosquito sampling. The content of the traps was collected and stored in a freezer (-20 °C) until further examination, upon which all specimens were identified at the species level under a microscope by the same expert taxonomist based on morphological characteristics (Kenyeres and Tóth 2008; Briët et al. 2021). The specimens have been sexed based on their morphology, but for the current study, counts for females and males were combined. During the identification procedure, the list of species and the abundance of each species (i.e., the number of individuals) were determined for each trap (see Table 1 for descriptive statistics). The comprehensive and systematic approach for trapping and identification allowed us to gather a large dataset, providing a robust basis for our analysis and conclusions. 169 NeoBiota 103: 165–185 (2025), DOI: 10.3897/neobiota.103.165442 Zoltán Soltész et al.: Co-existence patterns between invasive and native mosquitoes Importantly, we used identical BG-Sentinel traps with the same CO2 and lure configuration at each location, thereby ensuring methodological uniformity; thus, we compare the composition of mosquito communities as referred from the trap samples across sites with different abundances of invasive mosquitoes. Climate data Georeferenced climatic data were gathered for each sampling location using the Hungarian Meteorological Service (HungaroMet) open Meteorological Database (odp.met.hu). The meteorological data were generated by MISH interpolation methods from the measured and quality-controlled, homogenized, and completed data (grid resolution: 10 × 10 km; see for more details: Szentimrey et al. 2005; Izsák 2023). We gathered site-specific temperature (daily average, in °C with 0.01 accuracy) and precipitation (daily sum, in mm with 0.01 accuracy) data from 30 days preceding the trapping date in the respective year. Urbanization index Based on the geographic coordinates of each sampling site, we calculated the urbanization index within the surrounding area (i.e., 1 × 1 km square). For this purpose, we used the ‘UrbanizationScore’ software (Czúni et al. 2012) that scores the abundance of vegetation, buildings and paved roads based on the corresponding aerial images from Google Maps. The program then combines this information into a principal component that arranges the study sites along an urbanization gradient. Figure 1. The localities that were selected to sample mosquito communities by using adult mosquito traps in the field in Hungary. The traps were operating at least for one night. The filled dots represent the permanent traps (operating continuously for several months), while the open dots indicate the short-term traps (operating temporarily for a few days only). 170 NeoBiota 103: 165–185 (2025), DOI: 10.3897/neobiota.103.165442 Zoltán Soltész et al.: Co-existence patterns between invasive and native mosquitoes Proximity to water surface Based on the geographical coordinates, we calculated the distance between each trap location and the nearest surface water body (river, stream, lake, or pond) using QGIS 3.28. Distances were measured as straight-line (Euclidean) distances based on a hydrographic layer, and were later used as environmental variables in the analysis. The distance from the closest water surface was estimated in meters and was log10-transformed for the statistical analyses. Table 1. The number of individuals of mosquito species trapped between 2020 and 2023, and the number of settlements and traps where each species was captured within the short-term trapping campaign. For the long-term trapping campaign performed at four locations, only the total number of individuals captured for each species is shown. The scientific names of mosquitoes are written based on Snow and Ramsdale (2003). * Indicates invasive species, for which data were not used in this study. SHORT-TERM TRAPS PERMANENT TRAPS specimens settlement settlement % trap trap% specimens Aedes albopictus 853 26 13.54 96 18.05 9040 Aedes cinereus 0 0 0 0 0 2 Aedes japonicus* 38 16 8.33 19 3.57 10 Aedes koreicus* 325 58 30.21 95 17.86 324 Aedes rossicus 0 0 0 0 0 2 Aedes vexans 3860 104 54.17 196 36.84 1097 Anopheles claviger 4 4 2.08 4 0.75 25 Anopheles hyrcanus 34 11 5.73 11 2.07 0 Anopheles maculipennis s.l. 62 16 8.33 21 3.95 22 Anopheles plumbeus 102 29 15.1 38 7.14 506 Coquillettidia buxtoni 1 1 0.52 1 0.19 5 Coquillettidia richiardii 476 25 13.02 39 7.33 289 Culex hortensis 0 0 1.56 0 0 14 Culex martinii 1 1 0.52 1 0.19 0 Culex modestus 80 21 10.94 26 4.89 75 Culex pipiens s.l. 42140 188 97.92 498 93.61 43437 Culiseta annulata 199 39 20.31 49 9.21 20 Culiseta longiareolata 27 10 5.21 15 2.82 0 Ochlerotatus annulipes 2 2 1.04 15 2.82 189 Ochlerotatus caspius 679 54 28.13 72 13.53 110 Ochlerotatus cataphylla 0 0 0 0 0 3 Ochlerotatus detritus 0 0 0 0 0 1 Ochlerotatus dorsalis 2 1 0.52 2 0.38 50 Ochlerotatus geniculatus 18 13 6.77 15 2.82 269 Ochlerotatus pulcritarsis 4 4 2.08 2 0.38 8 Ochlerotatus pullatus 0 0 0 0 0 28 Ochlerotatus sticticus 0 0 0 0 0 172 Ochlerotatus punctor 0 0 0 0 0 2 Uranotaenia unguiculata 4 4 2.08 4 0.75 1 TOTAL 48911 192 532 55701 171 NeoBiota 103: 165–185 (2025), DOI: 10.3897/neobiota.103.165442 Zoltán Soltész et al.: Co-existence patterns between invasive and native mosquitoes Statistical analyses From the trap samples, we calculated the following variables reflecting the composition of the mosquito fauna for each trap originating from the direct fieldwork, if at least one individual for any native species were caught: i) species richness of the native mosquito fauna, ii) Shannon index to characterize the diversity of the native mosquito fauna by considering their relative abundance. We also calculated the abundance of Ae. albopictus and each native species that was captured at least once in the traps. Abundance values were log10-transformed for the statistical analyses. First, we tested for the relationship between the abundance of Ae. albopictus and estimates that reflect the composition of the native mosquito community. This was done by testing for the correlation of these variables, and also by constructing mixed-effects models with spatial correlation structure, in which species richness or diversity index was entered as the response variable. In each model, the focal predictor variable was the abundance of Ae. albopictus (log10-transformed), and we also included detection date (circular variable using the sine and cosine of the radians of the actual date to define seasonal rhythms) to account for temporal effects. Given that the data were geographically distributed, ecological conditions as well as the composition of the mosquito community could be more similar between closely situated sampling locations than between distantly positioned traps. Therefore, we defined an exponential spatial correlation structure for the residuals based on the geographical coordinates of the sampling sites. In this way, the pseudo-replication caused by the traps operating at the same locations between collection events was also considered. To control for temporal non-independence of data due to year effects (data from the same year may be more similar than from different years), we set the random effect term based on year as a categorical variable as a random effect. The spatial mixed-effects models were performed using the statistical package “nlme” (Pinheiro and Bates 2025) in the R statistical environment. Second, we investigated if any relationships between particular pairs of species can be observed in the data. For this, we examined if detected co-existence patterns between pairs of species followed a random expectation or shifted towards a positive or negative direction. Accordingly, we counted the traps that successfully captured Ae. albopictus or the given native species being compared (i.e., we identified at least one individual in the content of the trap) – independently of each other. Based on these observed incidences, we separately generated random scenarios for the presence of the two species along the sampling localities. We repeated these simulations 1,000 times, and in each run, we recorded how often the two species appeared together in the same traps purely by chance. These estimates define the null distribution of their expected co-occurrence, which was used as a statistical reference against the observed number of instances when both species were captured in the same trap. An observed number of co-occurrences lower than the 2.5th percentile of the generated random distribution indicates a negative association between the two species, whereas co-occurrences exceeding the 97.5th percentile of the null distribution suggest a positive association. Third, to investigate if the significant relationships between the presence of species are mediated by a third variable that reflects common environmental conditions or by direct interspecific interactions, we fitted path analysis models. More specifically, by using the R package “piecewiseSEM,” (Lefcheck 2016), we applied a piecewise structural equation modelling approach to distinguish between direct and indirect pathways, thus to make inferences about the causal associations among temporal variation in 172 NeoBiota 103: 165–185 (2025), DOI: 10.3897/neobiota.103.165442 Zoltán Soltész et al.: Co-existence patterns between invasive and native mosquitoes activity, environmental factors and the abundance of Ae. albopictus and native species. This analysis/approach relied on the following 3 hypotheses: i) environmental conditions determined by climate and habitat characteristics establish the ecological prerequisite for the population growth of Ae. albopictus (i.e., environmental variables directly affect the abundance of Ae. albopictus); ii) native mosquitoes are also sensitive to such environmental conditions, thus the same climatic and habitat variables determine the abundance of native mosquitoes; iii) the abundance of Ae. albopictus can also have a partial impact on the abundance of native mosquitoes if the introduction and spread of the invasive species directly interacts with native populations. To fit models for the above hypotheses, we relied on linear mixed-effects models with gaussian error terms available in the package “nlme” (Pinheiro and Bates 2025) that allowed incorporating random effects as well as accounting for spatial autocorrelation embedded in the geo-referenced data. In the first model incorporating predictions for hypothesis i), the response variable was the abundance (log10-transformed) of Ae. albopictus, and the predictor variables included detection date to reflect seasonal effects (we treated date as a circular variable by using the sine and cosine of the radians of the actual date) and the environmental variables such as temperature (daily temperature averaged over 30 days prior to trapping), precipitation (precipitation over 30 days prior to trapping, log10-transformed), urbanization (urbanization score) and distance from water habitats (log10-transformed). We also included the interaction between temperature and precipitation, because in hot weather, water surfaces evaporate faster, and also because the positive effect of temperature should be more robust when the optimal breeding habitats are available (i.e. there is some rain that fills the small containers). An exponential spatial correlation structure, based on the geographical coordinates of the traps, was used to account for the spatial autocorrelation of data, while the pseudoreplicative effect of within-year variations were handled by defining an appropriate random effect structure based on year categories. The other model incorporating predictions for hypotheses ii-iii) was fit for the abundance of the native species (log10-transformed), and had a structure very similar to the above model; the only exception was that it also included the abundance of Ae. albopictus (log10-transformed) as a predictor variable. Before fitting the structural equation model, structural equations were simplified based on a manual backward stepwise procedure, by which non-significant predictors were removed one by one. We expected that seasonal variations primarily impact temperature, that they also depict fluctuations on a short-term time scale, thus we specified correlated errors for detection date (the sine and cosine of the radians) and temperature. For the path analysis, we only considered species, for which the pair-wise analysis of associatedness indicated significant deviations either in the positive or negative direction, and the distribution of data allowed this complex modelling (i.e., we did not proceed with species, which were detected in very few or too many trap samples, as these would have caused highly unbalanced distributions). Results The composition of the native mosquito fauna In the raw data, there was no significant association between the abundance of Ae. albopictus and species richness of the native mosquito fauna (r = 0.009, N = 1517, P = 0.738). A similar result was found for Shannon diversity index (r = 0.023, N = 1517, P = 0.367). However, when we only included sites where 173 NeoBiota 103: 165–185 (2025), DOI: 10.3897/neobiota.103.165442 Zoltán Soltész et al.: Co-existence patterns between invasive and native mosquitoes the invasive species was present, these relationships were significant and positive (species richness: r = 0.281, N = 350, P < 0.001; diversity index: r = 0.263, N = 350, P < 0.001; Fig. 2). In addition, when we constructed a mixed effect model that appropriately accounted for the spatial and temporal structure of the data, we found that the abundance of Ae. albopictus was a significant predictor of the Shannon diversity index with a positive slope (Table 2). The presence of native mosquito species The co-occurrence of Ae. albopictus and Anopheles plumbeus was detected in 12 traps only. Ae. albopictus was present in 350 trap samples, while An. plumbeus was captured in 180 instances. We can generate a null-hypothesis from these observations in which we expect that both species will be present in 41–53 samples simply by chance with 95% confidence. The detected co-occurrence (12) of the two species was significantly lower than this random expectation (Table 3). Similar comparisons for other possible species pairs suggested that out of the 26 native mosquito species assessed, Ae. albopictus showed statistically significant associations with 11 species (based on random chance, we expected that 5% of the 26 relationships, i.e., 1–2 of them, would be significant). Table 2. The results of mixed-effects models with spatially correlated random effects testing for the association between the abundance of Aedes albopictus and estimates of the composition of the native mosquito fauna, while holding spatial and temporal effects constant. Species richness of the native mosquito fauna Fixed effects Estimate S.E. t-value P Intercept 1.768 0.252 7.028 < 0.001 Abundance of Ae. albopictus 0.088 0.062 1.425 0.154 sin(date) -0.372 0.059 -6.267 < 0.001 cos(date) 0.188 0.128 1.470 0.142 Random effects Variance parameters Year 0.192 Residual 1.442 Dimensions # of obs. 1517 # of groups 4 Shannon diversity index of the native mosquito fauna Fixed effects Estimate S.E. t-value P Intercept 0.175 0.052 3.352 < 0.001 Abundance of Ae. albopictus 0.077 0.020 3.813 < 0.001 sin(date) -0.032 0.015 -2.089 0.037 cos(date) 0.054 0.034 1.596 0.111 Random effects Variance parameters Year 0.006 Residual 0.146 Dimensions # of obs. 1517 # of groups 4 180 NeoBiota 103: 165–185 (2025), DOI: 10.3897/neobiota.103.165442 Zoltán Soltész et al.: Co-existence patterns between invasive and native mosquitoes species. Because BG-Sentinel traps target host-seeking females, their effectiveness partly depends on the proximity and composition of vertebrate host communities. Species with strong anthropophilic tendencies, such as Ae. albopictus, may be more frequently captured near human habitations, while ornithophilic or mammalophilic species might be underrepresented if their preferred hosts are scarce near trap sites. Furthermore, species differ in their ability to disperse from larval habitats to locate hosts, potentially decoupling adult presence from larval coexistence. Therefore, while adult mosquito assemblages offer valuable insights, they may not fully reflect larval-level interactions such as resource competition. This underscores the importance of integrating adult and larval surveillance to better infer ecological mechanisms underlying observed spatial patterns. Taken together, we have shown that Ae. albopictus shows remarkable co-occurrence patterns with several native mosquitoes in Hungary, and that its local abundance can display positive relationships with estimates of the diversity of the endemic mosquito fauna. However, by considering some key ecological factors and by applying a path analysis, we were able to demonstrate – at least for two species – that the detected negative associations are unlikely to reflect direct interaction effects between populations (e.g., competition), and that environmental filtering explains species co-occurrences. These insights emphasize the importance of using environmentally informed models to avoid misattributing ecological effects and to better distinguish environmental associations from potential competitive processes. Our study also highlights that the laboratory results suggesting competition between the larvae of different species do not necessarily translate into population patterns detected in the field for reproducing generations. Overall, our results imply that shared ecological preferences can facilitate long-term coexistence even in the presence of potential competitive interactions. Such dynamics may ultimately promote the establishment and persistence of invasive mosquito species in new habitats, offering important implications for invasion biology and vector surveillance strategies. To better understand the ecological mechanisms behind co-occurrence, future studies should adopt a more comprehensive approach that focuses on a broader range of environmental variables and also integrates species-specific morphological, behavioral, and life-history traits into the analytical framework. Such integrative models would help to disentangle the relative importance of environmental filtering, niche differentiation, and biotic interactions in structuring mosquito assemblages. Considering the complexity of invasion processes, incorporating these functional attributes may provide critical insights into the mechanisms that facilitate coexistence or promote displacement among native and invasive mosquito species. Acknowledgements We would like to thank all colleagues of the Mosquito Monitor team (www.mosquitosurveillance.hu) who participated in the field work and assisted during taxonomic identification, namely Ágnes Klein, Tamara Szentiványi, Beáta Újvárosi. Two anonymous reviewers provided valuable comments on a previous version of the manuscript. The study was supported by funds from the Hungary’s National Research, Develop ment and Innovation Office (K135841, PD-135143, RRF-2.3.1-21-2022-00006) and the Sustainable Development and Technologies National Programme of the Hungarian Academy of Sciences (NP2022-II-5/2022). 181 NeoBiota 103: 165–185 (2025), DOI: 10.3897/neobiota.103.165442 Zoltán Soltész et al.: Co-existence patterns between invasive and native mosquitoes Additional information Conflict of interest The authors have declared that no competing interests exist. Ethical statement No ethical statement was reported. Use of AI No use of AI was reported. Funding Authors were supported by funds from the Hungary’s National Research, Development and Innovation Office (K135841, PD-135143, RRF-2.3.1-21-2022-00006) and the Sustainable Development and Technologies National Programme of the Hungarian Academy of Sciences (NP2022-II-5/2022). Author contributions ZS and LZG conceived the main ideas, ZS performed literature review, ZS and LZG designed methodology for sampling, ZS, GM, NG, ZK collected the data, ZS performed mosquito identification, LZG analyzed the data, ZS and LZG wrote the first draft of the manuscript. All authors contributed critically to subsequent versions and gave final approval for publication. Author ORCIDs Zoltán Soltész https://orcid.org/0000-0003-3423-9258 Zoltán Kenyeres https://orcid.org/0000-0002-0941-7254 Gábor Markó https://orcid.org/0000-0003-1351-4070 Gergely Nagy https://orcid.org/0000-0002-0943-2876 László Zsolt Garamszegi https://orcid.org/0000-0001-8920-2183 Data availability All of the data that support the findings of this study are available in the main text. 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Journal of Medical Entomology 59: 843–854. https://doi.org/10.1093/jme/tjac023 Supplementary material 1 Basic data forming the basis of the analysis Authors: Zoltán Soltész, Zoltán Kenyeres, Gábor Markó, Gergely Nagy, László Zsolt Garamszegi Data type: xlsx Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/neobiota.103.165442.suppl1