Water drains act as cryptic but prolific mosquito larval habitats and are often the most productive breeding sites in urban landscapes. Understanding how climate and water infrastructures interact to shape these breeding habitats is essential for controlling vectors like Aedes albopictus. Across two mosquito seasons (2023-2024), we monitored drains in a managed (with vector control) botanical garden and an unmanaged residential area to quantify water dynamics and larval presence. We identified discharge outlet height as the critical structural determinant of water retention: drains with outlets near the basin floor rarely retained water, preventing mosquito breeding. Median water residence time was a strong predictor of larval presence, even under active vector control treatments; treated drains with residence times exceeding 7 days exhibited larval positivity rates 7.7 times greater than those with shorter residence times. To associate weather with drain-scale hydrological dynamics, we developed a mass-balance approach to compute a Water Storage Index (WSI), capturing the proportion of stagnant water across a drain network. Our analysis revealed a prolonged system's response, where rainfall adds water rapidly, whereas evaporation removes it slowly, both being equally relevant drivers of water dynamics. The WSI effectively scaled these climatic variables into a metric of network-wide breeding capacity. We propose lowering discharge outlet as a primary prevention strategy. Where water retention persists, median water residence time and the WSI serve as complementary ecological indicators to identify high-risk drains and periods of elevated larval carrying capacity, providing a scalable framework for anticipating mosquito-borne disease risk under intensifying climate variability.

Understanding the fitness advantages conferred by eusociality remains a central challenge in behavioral ecology. One promising approach is to identify collective strategies that shift efficiency within social groups. Here, we test the hypothesis that reserve workforces in eusocial insect colonies represent an adaptive mechanism that enhances flexibility and foraging efficiency under fluctuating environmental conditions. We examine how such reserve workers modulate the departure and return rates of foragers and how these time-dependent dynamics shape the colony’s overall energetic balance. By integrating an energetic-balance framework with stochastic search simulations inspired by empirical results from Aphaenogaster senilis , we quantify the energetic requirements for colony viability, incorporating energy intake, search costs, and basal metabolic demands. Our results show that as colonies grow, maintaining a positive energy balance requires a disproportionately larger relative workforce. By modulating departure and return rates over time, colonies control the synchrony of their collective search and efficiently activate or suppress their reserve workforce to scale foraging effort as needed. These findings suggest that the “lazy” or weakly engaged workers commonly observed in large colonies function as an essential reserve that stabilizes colony energetics and enhances responsiveness. Together, our results provide a functional explanation for sublinear metabolic scaling in eusocial groups and highlight workforce modulation as a key factor underlying their energetic stability and evolutionary success.

Mosquito-borne diseases are rising globally, driven in part by the expanding range of invasive vector species. However, the mechanisms underlying their spread remain poorly understood, largely due to limited and inconsistent data. Here, we integrate high-resolution human mobility data with a thermo-biologically realistic metapopulation model to investigate the colonisation dynamics of the dengue vector, Aedes albopictus, using 20 years of invasion data from Spain. Our results reveal the dual role of humans: as architects of climate change, making local environments increasingly suitable, and as vehicles of dispersal, inadvertently transporting this vector across regions. The spread occurs through a fragmented human mobility network, while natural dispersal bridges gaps between connected areas, enabling faster and more continuous expansion. These findings underscore the importance of considering the synergistic effects of climate, human movement, and natural dispersal when forecasting future range expansions and designing coordinated, multi-scale vector control strategies in an era of rapid environmental change.

BackgroundThe Asian tiger mosquito, Aedes albopictus, is an aggressive invasive vector responsible for transmitting important arboviruses. Its global spread has been largely facilitated by human-mediated transport, especially through trade and road networks. Since its first detection in the Netherlands in 2005, repeated introductions have occurred via pathways such as lucky bamboo imports, used tires, aircraft, and ground traffic. Despite ongoing surveillance and elimination efforts, uncertainties remain about the origins, recurrence, and establishment potential of these introductions.MethodsWe analyzed 200 Ae. albopictus specimens collected from 21 locations in the Netherlands from 2014 to 2023, including detections in residential areas and points of entry (PoEs). Samples were genotyped at 19 specific microsatellite loci. Genetic diversity and kinship were studied to better understand genetic structure, relatedness between and within locations, and local overwintering. We also determined the presence of Wolbachia endosymbiont strains in the specimens by sequencing Wolbachia markers.ResultsGenetic structure and kinship analyses revealed multiple independent introductions, genetic diversity among sites, and evidence of local overwintering at both residential and PoE locations, including used tire storage sites. Close-kin relationships were identified in 63 specimen dyads. Among these, one dyad confirmed overwintering at a used tire storage facility, four indicated kinship within a residential area, and two between two locations. Genetic assignment results also highlighted successful elimination of the species in one Dutch residential area. A total of 16 Dutch locations (76.19%) tested positive for the presence of Wolbachia. Overall, 48.86% specimens analyzed tested positive for at least one strain, and 35 close-kin dyads showed complete concordance in Wolbachia infection status.ConclusionsOur findings highlight the complex invasion dynamics of Ae. albopictus in the Netherlands. Our results demonstrate that microsatellite analysis, combined with kinship assessment, is an efficient approach for investigating kinship among individuals within and between urban areas and PoEs, providing evidence of local overwintering, and assessing the genetic structure of Ae. albopictus at introduction sites. The widespread presence of Wolbachia, which is known to reduce mitochondrial diversity, suggests that mitochondrial DNA (mtDNA)-based population analyses may be limited for the species.

West Nile virus (WNV) is one of the most widespread arboviruses globally and is maintained primarily through a bird-mosquito-bird transmission cycle, while other vertebrates play more limited roles. Host contributions to transmission depend on both infection evidence in natural populations (reflecting exposure and susceptibility) and reservoir competence, determined by the magnitude and duration of viraemia sufficient to infect mosquitoes. Despite extensive surveillance and experimental research, no comprehensive, standardised resource has integrated evidence on host exposure and infection in natural populations together with experimental data on host competence across vertebrate taxa. Here, we present two harmonised datasets compiled through a systematic literature review: (i) a WNV host prevalence dataset, summarising infection and serological evidence in wild and captive vertebrates; and (ii) a WNV host competence dataset, derived from controlled experimental infections. The prevalence dataset aggregates records from 541 studies across 91 countries (1950-2023), comprising 535,568 tested individuals from 1,801 vertebrate species. The WNV host competence dataset compiles 113 experimental infection studies covering 103 species and 3,030 individuals, and provides standardised time-resolved viraemia and survival data with accompanying metadata, enabling reconstruction and/or modelling of species-specific viraemia trajectories and the derivation of quantitative competence metrics. Both datasets use standardised taxonomy and incorporate synonym crosswalks to facilitate linkage with trait databases, phylogenetic trees and species distribution products. Together, these resources provide a unified foundation for macroecological analyses, surveillance gap assessment, and modelling multi-host WNV transmission dynamics.

The Mosquito Weather Index (MWI) is the first operational index to translate the combined effects of temperature, humidity and wind speed into a single measure of mosquito activity, communicated to the public and public-health stakeholders in an easy-to-act-on form. The index ranges from 0 to 1 and maps to five activity levels, from "no activity" to "very high activity." This study presents the first empirical evaluation of the MWI. We assess its predictions of vector mosquito counts from adult suction traps in Moschato-Tavros, Attica, Greece, during 2018 and 2019. We find the MWI is strongly associated with Aedes albopictus and Culex pipiens trap counts. The single MWI variable improves predictions of trap counts---both in cross-validation and in forward forecasts---from models that lack information on weather or seasonality, while adding little once such information is included. We also evaluate different methods, finding that temporally fine-grained (hourly) weather data is crucial for its performance. These findings suggest that the MWI functions as intended, offering a simple, interpretable predictor of vector mosquito activity that can be acted on by the general public and mosquito-control specialists.

As mosquito-borne diseases continue to expand worldwide, integrating citizen science into vector surveillance presents untapped potential. This study compares ecological models of Aedes albopictus, an invasive mosquito and global vector of dengue and other arboviruses, in Spain (2020-2022), using two contrasting data sources: traditional traps and citizen science. While both showed strong seasonal agreement, spatial discrepancies emerged in summer, particularly in northwestern Spain. These differences were linked to the broader environmental coverage provided by citizen scientists' observations, especially under extreme temperature and humidity conditions. Citizen scientists can report mosquito activity in places and times where traps are absent or ineffective, capturing real host-seeking behavior and reducing sampling biases inherent to fixed trap locations. Incorporating citizen science data into trap-based models improved monthly predictive performance, demonstrating its value as a complementary source. Combined, traditional traps and citizen science enhance mosquito surveillance, support early warning systems, and inform decisions under climate-driven range expansion.

Native to East Asia, the Asian bush mosquito (Aedes japonicus) has recently expanded its global range, with established invasive populations in Europe and North America. Given its potential role as a vector of various arboviruses, understanding its invasion process and ecological dynamics is crucial for managing its spread and mitigating public health risks. In the Iberian Peninsula, the species was first detected in Asturias in 2018 and has since expanded to neighbouring regions. Here, we elucidate the invasion pathways and possible origins of Ae. japonicus populations in Spain using sequence data and microsatellite markers, and by screening for the presence of maternally transmitted bacteria of the genus Wolbachia. We analysed 635 Ae. japonicus from 14 countries, including Japan (native range), the United States, and 12 European countries. No clear association between haplotypes and geographical location was detected in any of the three genes analysed (nuclear ITS2, mitochondrial COI and ND4). Wolbachia was not detected in any of the screened samples. In contrast, microsatellite-based population structure analyses showed that most Spanish samples clustered closely with those from College Park, Maryland (USA), located near the Port of Baltimore, one of the largest ports in the United States and a recognised gateway for invasive species introductions. Northern Spain hosts major seaports such as Bilbao and Gijón, whereas the nearest established Ae. japonicus population in Europe lies over 1,000 km away in northeastern France. Taken together, these findings suggest that the most plausible invasion route of Ae. japonicus into Spain involves maritime transport from the eastern coast of the United States to northern Spanish ports, likely accompanied by additional minor introductions of European origin. The inclusion of additional microsatellite loci originally developed for Ae. albopictus yielded results consistent with those obtained using Ae. japonicus-specific loci, reinforcing the robustness of the observed patterns. This work provides new insights into the invasion process of Ae. japonicus in Europe and highlights the need for continuous monitoring and tailored interventions at key ports of entry.

Abstract Biological control of mosquitoes using aquatic predators offers a sustainable alternative to chemical insecticides, yet the specific predator and prey functional traits that govern consumption efficacy remain poorly quantified at a global scale. We conducted a global meta-analysis of 755 effect sizes across 59 studies to evaluate how predator identity (fish vs. odonate naiads), body size, dietary guilds, and prey characteristics influence consumption rates. Using multilevel models and robust publication-bias corrections, we quantified predation efficiency, expressed throughout as the consumption rate (CR, larvae predator □¹ h □¹), while accounting for methodological variations across experimental designs. The primary literature itself proved geographically skewed towards Asia (chiefly India), with Africa, the Americas, and Europe markedly under-represented. Grouping predators solely by broad taxonomic identity concealed the central pattern in our data. Although naiads outperformed fish when compared directly within the same studies, this taxon-level difference was driven almost entirely by non-mosquitofish species, the least efficient predator group overall. Mosquitofish ( Gambusia spp.) and dragonfly naiads were statistically indistinguishable from one another, indicating that dietary specialisation, not taxonomic identity, is the stronger predictor of predation efficacy. Predator body size strongly and positively predicted consumption rates in naiads—driven primarily by dragonflies—but showed no significant or negative relationship in fish. Methodological traits heavily structured the extreme heterogeneity observed across studies; notably, exposure time acted as a severe rate-suppressor, where prolonged assays drastically underestimated per-hour consumption rates due to satiety or handling constraints. Nevertheless, a combined model incorporating all significant ecological moderators simultaneously explained a substantial share of the between-study variance, confirming that predator-prey dynamics in these systems are highly predictable from functional traits. Effective biological control cannot rely on broad taxonomic assumptions but requires evidence-based trait-matching. Management programs should prioritise body size when deploying insect predators, selecting the largest individuals within species known to consume mosquito larvae and favour insectivorous fish species over generalists. Crucially, because short-term laboratory assays artificially inflate efficacy, multi-duration assessments are essential to accurately scale up biocontrol predictions from experimental arenas to complex, real-world ecosystems.

Task allocation in eusocial insects has long been studied under the framework of division of labor, implying a relatively rigid association between individuals and tasks. However, most eusocial species lack morphological specialization, and workers regularly switch tasks as colony demands change. This raises a fundamental question: do tasks shape the behavioral profiles of workers, or does individual behavioral variation cut across task boundaries? We addressed this in a controlled laboratory study of Aphaenogaster senilis ants, comparing the behavioral profiles of four task groups (scouts, recruits, nurses, and necrophores) spatially segregated by their location within the colony setup and subsequently tested individually in four ecologically relevant contexts. This multivariate profiling, still rarely applied in ants, revealed that some tasks impose clear behavioral specialization (scouting, brood care), whereas others do not (recruitment, necrophoresis). Critically, this specialization appears in foraging-related tasks, whereas sociality does not: it varies considerably among workers, even within a single task group. Behavioral specialization, therefore, exists, but not across every dimension of behavior, and it is not a fixed property of the task. These results suggest that workers may differ in their readiness to shift roles depending on the task at hand, and this variation may in turn shape how colonies adapt to environmental change. More broadly, our results speak to a question central to collective behavior research well beyond ants: how individual variability translates into functional structure at the group level.

Understanding mosquito activity in dense urban areas is essential to assess human exposure to nuisance and health risks. We analyzed real-time mosquito data from four smart traps operating between 2021 and 2024 in Barcelona (NE Spain), focusing on the fine-scale temporal dynamics of two major urban vector species, Aedes albopictus and Culex pipiens. Both species exhibited consistent bimodal diel activity patterns aligned with sunrise and sunset, with species-specific differences in peak intensity and timing as well as seasonal fluctuations. Using a random forest framework, we identified light-related cues as primary activators of mosquito host-seeking activity; and light cues, temperature and rainfall also acting as modulators of activity, roles varying by species and temporal scale. This activator-modulator perspective illustrates how intrinsic circadian rhythms interact with extrinsic environmental drivers to determine mosquito activity across temporal scales. Our findings highlight the ecological value of high-resolution monitoring and the potential of next-generation surveillance tools to support early warning systems and evidence-based vector control in the context of smart cities.

Liquid brains conceptualize living systems that operate without central control, where collective outcomes emerge from local and dynamic interactions. This concept extends beyond ants and other social insects to include immune systems, slime molds, and microbiomes. In such systems, connectivity scales with population density, facilitating more efficient information transfer as group size increases. However, in sparse conditions, where fewer individuals interact, movement likely plays a crucial role in shaping connectivity, ensuring optimal collective efficiency. We tested this hypothesis during the foraging process of Aphaenogaster senilis, an ant species that does not primarily rely on chemical communication. We empirically measured ant movement behavior and characterized their foraging dynamics across large spatiotemporal scales, closely reflecting the species' natural ecology. Integrating observed movement heterogeneity into a neuronal-like model, we quantitatively replicated ants foraging efficiency and spatiotemporal dynamics. Our results reveal that a simple feedback mechanism, mediated by local interactions, governs the foraging patterns of A. senilis. Such feedback is modulated by adjusting the proportion of two coexisting movement behaviors: recruits, which facilitated information transfer and food exploitation by aggregating closely to the nest and the food patches, and scouts, which could bypass this feedback and discover alternative food sources. Therefore, distinct movement patterns contributed differently to optimizing each phase of the foraging process, proving an adaptive mechanism to balance exploration and exploitation. Our findings underscore how incorporating specific biologically grounded insights into complex systems frameworks, enhances our understanding of the mechanisms underlying collective intelligence in biological systems.

Behavioral heterogeneities in animals, also known as syndromes, play a crucial role in understanding how natural populations flexibly adapt to environmental changes. In ant species like Aphaenogaster senilis, two key roles in collective foraging are commonly recognised: scouts, who discover food patches, and recruits, who exploit these patches and transport food back to the nest. These roles involve distinct movement patterns and exploratory behaviours. In this chapter, we develop a correlated random walk model on a bounded honeycomb lattice to interpret and replicate empirical observations of foraging ants in an enclosed arena with honeycomb tiling. We do so by extending the theory of first-passage processes for 𝒩 random walkers when individuals belong to a heterogeneous population. We apply this theory to examine how individual behavioural heterogeneity in ants affects collective foraging efficiency, focusing on first-passage time statistics for nest-to-patch and patch-to-patch movements. With the combined use of the mathematical model and the controlled experimental setup we evaluate (i) the impact of distinct movement strategies by scouts and recruits on finding food items and (ii) whether ants practice strict central place foraging or utilise previously discovered patches as starting points for further exploration.

The rise in mosquito-borne diseases such as dengue, Zika, and chikungunya, exacerbated by the ever-expanding habitats of Aedes albopictus, poses a significant public health risk. Even marginal improvements in vector control efficacy can be crucial in mitigating these risks. In this study, we employed a metapopulation model to simulate Ae. albopictus population dynamics and dispersal, optimizing the timing and spatial allocation of larvicidal treatments. Simulations revealed that larvicide treatments are most effective when applied preventively, early in the mosquito season, particularly under conditions of lower-than-average cumulative rainfall and, to a minor extent, colder-than-average temperatures, as these conditions limit larvae proliferation. We found that breeding site characteristics, particularly surface area and maximum water holding capacity, are critical in determining optimal treatment allocation in scarce-resource scenarios. However, a cost-effectiveness trade-off exists, as larger breeding sites offer more substantial reductions in mosquito populations but also demand higher larvicide dosages. Spatial factors such as breeding site distribution had minimal impact on treatment efficacy, possibly due to the high mobility range of adult mosquitoes compared with the size of the study area. Our results highlight the superior efficiency of the optimized approach in comparison with routine vector control strategies, especially when resources are limited, offering a more effective use of larvicide in controlling mosquito populations. This study demonstrates that vector control strategies for Ae. albopictus can be significantly enhanced by considering climatic variables and breeding site characteristics in treatment planning. This research provides a framework for developing cost-effective and flexible mosquito control programs that can adapt to environmental conditions, potentially improving public health outcomes by reducing the transmission risk of mosquito-borne diseases.

Mosquito-associated microbiota are influenced by a number of factors, e.g., geography, host species, and developmental stage. Understanding these microbiotas is crucial for assessing their role as vectors and in pathogen dissemination and most studies have largely focused on a few model species, while others like Aedes japonicus remain poorly characterized. Here, we compared the bacterial communities of Aedes albopictus and Aedes japonicus across eight countries: six in Europe, plus the USA and Japan, from both adults and larval stages when possible, using 16S rRNA amplicon sequencing. We found large differences in microbiota composition between mosquito species, with Ae. albopictus exhibiting lower bacterial diversity than Ae. japonicus . Geographic variation in bacterial diversity was also evident, with mosquitoes from Japan and the Netherlands harbouring the most diverse bacterial communities, while Austrian populations displayed the lowest diversity. Developmental stage (adults and larvae) had the strongest influence on bacterial composition, with aquatic-associated genera such as Limnohabitans and Aeromonas dominating larvae, whereas adult mosquitoes harboured higher abundances of Acinetobacter and Methylobacterium . No association was found between Aedes species genetic distance, determined by relatedness, and the bacterial community compositions. A number of bacterial genera with known pathogenic potential, including Pseudomonas , Serratia , Klebsiella , and Acinetobacter , were detected across multiple locations, suggesting that mosquitoes could serve as environmental reservoirs for opportunistic and antimicrobial-resistant bacteria. We identified Wolbachia in Ae. albopictus from Spain and Italy and at low abundances in Ae. japonicus from the USA and Japan, marking one of the first reports of Wolbachia in this species. This is, to our knowledge, the most comprehensive study on Ae. japonicus microbiotas. Our findings provide insights into the ecological and epidemiological implications of mosquito microbiota and emphasize the need for further investigation into their role in pathogen transmission and antimicrobial resistance dissemination.

The rising incidence of arboviral diseases poses a public health challenge worldwide. However, local-scale interactions among vectors, hosts, and the environment remain poorly understood. In this study, we analyzed historical, multi-source data to assess pathogen transmission risk in a Mediterranean wetland of Northeastern Spain, examining mosquito vectors, avian hosts for West Nile virus (WNV), and human hosts for dengue, Zika, and chikungunya. Mosquito activity peaked between June and October. Aedes albopictus was predominant in urban areas, whereas Culex species were more prevalent in rural and natural environments. The relative abundance of passeriform and columbiform bird species influenced potential amplification and dilution phenomena in the WNV enzootic cycle. We developed a spatial risk index for WNV transmission by integrating vector abundance and avian community composition. High-risk areas were identified near urban edges, particularly adjacent to rice fields and wetlands where mosquitoes and reservoir hosts overlapped. For dengue, Zika, and chikungunya, the highest transmission risk was observed in late summer, coinciding with the phenological peak of Aedes albopictus and the importation of cases from endemic regions. Collectively, these findings highlight the value of fine-scale ecological indicators for guiding targeted mosquito surveillance and control strategies to effectively reduce the risk of arboviral transmission in vulnerable Mediterranean regions.