The direct monitoring of mosquito populations in field settings is a crucial input for shaping appropriate and timely control measures for mosquito-borne diseases. Here, we demonstrate that commercially available mobile phones are a powerful tool for acoustically mapping mosquito species distributions worldwide. We show that even low-cost mobile phones with very basic functionality are capable of sensitively acquiring acoustic data on species-specific mosquito wingbeat sounds, while simultaneously recording the time and location of the human-mosquito encounter. We survey a wide range of medically important mosquito species, to quantitatively demonstrate how acoustic recordings supported by spatio-temporal metadata enable rapid, non-invasive species identification. As proof-of-concept, we carry out field demonstrations where minimally-trained users map local mosquitoes using their personal phones. Thus, we establish a new paradigm for mosquito surveillance that takes advantage of the existing global mobile network infrastructure, to enable continuous and large-scale data acquisition in resource-constrained areas.

Flight on the 2D air-water interface, with body weight supported by surface tension, is a unique locomotion strategy well adapted for the environmental niche on the surface of water. Although previously described in aquatic insects like stoneflies, the biomechanics of interfacial flight has never been analysed. Here, we report interfacial flight as an adapted behaviour in waterlily beetles (Galerucella nymphaeae) which are also dexterous airborne fliers. We present the first quantitative biomechanical model of interfacial flight in insects, uncovering an intricate interplay of capillary, aerodynamic and neuromuscular forces. We show that waterlily beetles use their tarsal claws to attach themselves to the interface, via a fluid contact line pinned at the claw. We investigate the kinematics of interfacial flight trajectories using high-speed imaging and construct a mathematical model describing the flight dynamics. Our results show that non-linear surface tension forces make interfacial flight energetically expensive compared with airborne flight at the relatively high speeds characteristic of waterlily beetles, and cause chaotic dynamics to arise naturally in these regimes. We identify the crucial roles of capillary-gravity wave drag and oscillatory surface tension forces which dominate interfacial flight, showing that the air-water interface presents a radically modified force landscape for flapping wing flight compared with air.

The lack of high-resolution field data on the abundance, species and distribution of mosquitoes is a serious impediment to effective control of mosquitoborne disease, yet the availability of high-throughput, low-cost surveillance techniques remains a bottleneck in generating such data. Here, we establish that commercially available mobile phones (including low-cost basic models) are a powerful tool to probe mosquito activity, by sensitively acquiring acoustic data on their species-specific wingbeat sounds, together with the time and location of the human-mosquito encounter. We survey a range of medically important mosquito species to quantitatively demonstrate how acoustic recordings supported by spatio-temporal metadata enable rapid, non-invasive species identification. As proof-of-concept, we carry out field demonstrations where minimally-trained users map local mosquito fauna using their personal phones. Thus, by leveraging the global mobile phone infrastructure with the potential for engaging citizen scientists, our approach enables continuous largescale acquisition of mosquito surveillance data in resource-constrained areas.Frequent, widespread, and high resolution surveillance of mosquitoes is essential to understanding their complex ecology and behaviour (1, 2), in order to predict disease risk and formulate effective control strategies against mosquito-borne diseases like malaria, dengue and Zika (3,4). Mosquito populations vary heterogeneously across urban and rural landscapes, further fluctuating with seasonal or climatic trends and human activities. Hence, the direct monitoring of mosquito species and abundance in field settings is necessary to shape appropriate and timely vector control measures (5,6). Yet, a paucity of such ecological data continues to remain a significant bottleneck in disease control efforts, particularly in resource-poor areas, since current surveillance techniques such as trapping and manual identification are labour, time, and cost intensive. Consequently, although there have been extensive efforts to map mosquito abundance using interpolative mathematical models, their field inputs from entomological surveys are comparatively sparse (7). Therefore, there is a crucial need for novel methods of surveillance that are extremely low-cost yet high-throughput, to adequately sample mosquito populations across large areas while simultaneously maintaining high spatio-temporal resolutions.A promising candidate to answer this need is acoustic monitoring, where the wingbeat sounds produced by mosquitoes in flapping-wing flight are used to identify different species in the field (8-12). This is based on the hypothesis that sexual selection has led to unique speciesspecific sound signatures for different mosquito species (13-18). However, the challenges of using expensive microphones to acquire low amplitude mosquito sounds against potentially high background noise levels pose a barrier to the widespread adoption of acoustic surveillance as a field technique (19-21). Low-cost technologies usi...

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