ISSN 0013-8738, Entomological Review, 2015, Vol. 95, No. 4, pp. 517–524. © Pleiades Publishing, Inc., 2015. Original Russian Text © D.N. Lapshin, D.D. Vorontsov, 2015, published in Zoologicheskii Zhurnal, 2015, Vol. 94, No. 6, pp. 661–669.
Temporal Dynamics of Host-Landing Rate in Mosquitoes Attacking the Imitation of a Host D. N. Lapshina and D. D. Vorontsovb a
Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, 127994 Russia e-mail:
[email protected] b Koltsov Institute of Developmental Biology, Russian Academy of Sciences, Moscow, 119334 Russia e-mail:
[email protected] Received March 12, 2014
Abstract—The rates of mosquito landing on a host-imitating device were measured. The device contained an electric heater to imitate the presence of a warm-blooded animal, a gauze screen impregnated with meat juice, a microphone with an amplifier to record the sounds of mosquito landings and take-offs, and a light meter to record the ambient illumination. In addition, the behavior of mosquitoes near the device was studied by video recording. All the experiments were conducted in the first half of June in evening and morning hours in mixed spruce-birch forests of Moscow region. Audio recordings were digitally analyzed to estimate the landing rates. Significant (more than 50% of the average) quasi-periodic fluctuations of the mosquito landing rate were revealed. The peaks of mosquito activity alternated with drops with an average period of 30 min (20–50 min in different recording sessions). These fluctuations were recorded in calm weather during a gradual change in illumination. Experiments with two similar devices positioned 20 m apart showed that fluctuations of mosquito activity developed independently at each site. The fluctuations in the mosquito landing rate seem to be largely determined by endogenous factors: mosquito females, failing to obtain blood from the host-imitating device, lost interest in it and landed to rest on the nearby vegetation. After 20–50 min, the memory trace of the previous experience gradually faded, and mosquitoes returned to the attracting device thus starting the next peak of activity. DOI: 10.1134/S0013873815040168
The activity rhythms of mosquitoes, as well as other animals, consist of two groups of components: exogenous and endogenous ones. The exogenous rhythms are determined by the external environmental factors, of which one of the most important is the daily rhythm (Aschoff, 1984; Chernyshev, 1984; Barrozo et al., 2004; Vinogradova and Karpova, 2010). The endogenous rhythms can be revealed under stable physical conditions in the laboratory (Jones et al., 1972) or under natural conditions, given that both environmental parameters and the animals’ behavior can be reliably recorded by the researchers. The daily fluctuations in the activity of bloodsucking mosquitoes have been studied for many years in all the climatic zones where these insects occur (Monchadsky, 1950; Popov, 1953; Kukharchuk, 1980; Khlyzova, 2006; Gündüz et al., 2009; Reshetnikov et al., 2009). It was shown by these studies that the intensity of attacks of most mass mosquito species varied in an adaptive way, first of all depending on the temperature dynamics that is more or less correlated with the illumination level.
In the temperate latitudes in the first half of summer, the mosquito attacks revealed two peaks: the evening and the morning one (Redkina and Ostroverkhova, 2007; Reshetnikov et al., 2009; Vinogradova and Karpova, 2010). The evening peak was usually more pronounced, though cases of a higher activity of mosquitoes in the predawn hours were also recorded (Barashkova and Reshetnikov, 2012). There are several techniques for assessment of intensity of mosquito attacks, among which the most common are: sweeping of the target (man or animal) with an entomological net, human landing catches with mosquitoes being collected in an aspirator (the Gutsevich method), and capture of attacking mosquitoes in a bell trap. In the latter case, the researcher who is also the bait is positioned under the raised gauze bell. After a 5-min exposure, the bell is quickly lowered to cover the bait, and the insects captured inside are collected. This method is known as the Monchadsky bell. An improved variant of the Monchadsky bell is the Berezantsev bell. In this technique, the bell itself is
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made of dark cloth, with a cage of light netting attached to its top. After the human bait is covered with the bell, the insects fly up and into the light cage, where they can be collected for counting and identification. The bait for the bloodsuckers is most often a human, less frequently some domestic animal: a cow or a horse. To estimate the degree of ornithophily of mosquitoes of the genus Culex, chickens placed in an insect trap were also used (Bezzhonova et al., 2004; Lopatina et al., 2007). In case of net sweeping, the standard parameter is the mean number of mosquitoes captured per 10 sweeps (Detinova et al., 1978; Guidelines…, 2012). Another method actively used in the past and still being employed consists in counting and collecting insects on an exposed forearm, the exposure time varying from 5 to 25 min depending on the intensity of attacks (Guidelines…, 2007). Thus, the most common techniques for assessment of mosquito activity are anthropocentric by their very nature, since they most often use the human bait. Correspondingly, the results obtained by such techniques characterize the degree of bloodsuckers’ attraction to man. It should be taken into account that, since researchers usually work together with assistants, mosquitoes within the distance of several meters are actually attracted by two persons rather than one. When the dynamics of mosquito attacks on animals is studied, at least one human is also present nearby and serves as an additional factor of attraction. Sweeping with an entomological net, movement of people, and even gestures may constitute positive stimuli for mosquitoes. However, bloodsucking arthropods in the temperate forests of Russia mostly feed on relatively small animals which comprise the majority of inhabitants of the boreal zone. The dynamics of mosquito attacks on these animals under natural conditions is still unknown. During assessment of mosquito activity near the bait, the collection and counting of insects may take considerable time. For this reason, consecutive surveys are usually performed with an interval of 1–2 hours. The common techniques are thus unsuitable for continuous estimation of the attack intensity at a time scale typical of the variation of abiotic factors, such as the illumination level during sunny spells and the associated fluctuations of wind velocity and direction. A host-imitating device, or “artificial animal,” was proposed earlier for attracting the mosquitoes and
measuring their activity near the potential host (Lapshin, 2012). This device had a self-contained power supply and included a gauze screen permeated with meat juice, a heater positioned under the screen, and an amplified microphone to record the sounds of attacking mosquitoes. The combination of heat and the meat odor proved to be an efficient attractor for bloodsuckers, despite the absence of a source of carbon dioxide which is regarded as one more important component triggering the mosquito attack (Kawada and Takagi, 2004; Klun et al., 2013). Already during the first tests of the “artificial animal” in the forests near Moscow, we recorded fluctuations of mosquito attacks with a period of about 40 min and a deviation amplitude of about 50% of the mean (Lapshin, 2012). Earlier, Alekseev and coauthors (1977) also noted a highly non-uniform dynamics of mosquito attacks. In view of this, we decided to perform continuous monitoring of the intensity of mosquito attacks on the imitated host, using different methods of recording their behavior. MATERIALS AND METHODS In this study we used the “artificial animal” device (below referred to as the Device) which attracted females of bloodsucking mosquitoes with heat and odor. The recording method implemented the previously proposed idea of using the flight sounds of attacking mosquitoes as indicators of their activity (Jones, 1964; Raman et al., 2007). The final results of acoustic signal processing were plots of the temporal dynamics of attack intensity, i.e., the number of attacks during each 5-min interval. The Device (Fig. 1) consisted of four main systems: a 2.5 W heater imitating the presence of a warmblooded animal, a heated gauze screen permeated with beef juice, a microphone with an amplifier to record the sounds of mosquitoes landing on the screen or taking off, and a light meter. The frequency of the output signal of the meter (Hz) was numerically equal to the illumination intensity (lx). The gauze screens were dried before the experiment. The heater of the Device was switched on 15 min before recording. The power was provided by a 6.3 V, 4 Ah battery. The measurements of the Device without the support and wiring were 8 × 7 × 7 cm. The experiments were carried out in the morning and evening hours, from 1 to 18 June, 2011–2013, in mixed spruce-birch forests of Moscow region, within ENTOMOLOGICAL REVIEW Vol. 95 No. 4 2015
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several tens of meters from the forest and field boundary. In all, we performed 12 measurement sessions 2.5 h each, 10 of them in the evening (19:00–21:40) and 2 early in the morning (5:00–7:30). The experiment sites and the nearest inhabited localities were as follows: 55°41'N, 36°41'E, Zvenigorod Biological Station of Moscow State University; 55°19'N, 36°40'E, Bashkino; 56°12'N, 36°50'E, Zamyatino; 55°30'N, 36°53'E, Rassudovo; 55°14'N, 37°44' E, Yusupovo. During eight measurement sessions we simultaneously used two identical Devices positioned about 20 m apart and performed dual-channel recording of the attacking mosquitoes. The Devices were placed at an elevation of 25 cm from the gauze screen plane to the soil surface. The distance from the tent with researchers to the nearest Device was no less than 12 m. The use of a tent with an extra canopy was a necessary condition, otherwise the mosquitoes would sense the presence of humans which might affect the results. Days with dry windless weather were selected for experiments. The air temperature during the experiments was 11–19°C. The humidity at the height of the Device varied from 60 to 75% in the evening and from 90 to 70% in the morning. The air temperature and humidity at the experiment sites were monitored using a DT-8820 multifunction environment meter (CEM, China). During the sessions, video and acoustic recording of the insects attacking the Device was performed. The signal from the output of the microphone amplifier supplemented with that from the light meter was fed to the Zoom H2 digital recorder (Zoom Corp., China). The video signal from the camera was also transmitted by cable to a portable monitor or a laptop installed in the tent. The acoustic recording system proved to be sensitive to noise from various sources, such as trains, cars, and aircraft. Therefore, we selected the experiment sites located far from highways with heavy traffic, railroads, and airfields. At the first stage of acoustic record processing, we used frequency filtering (Sound Forge 10 Pro software, Sony, Japan) to isolate the spectral components corresponding to the second harmonic of the sounds of mosquito females flying near the gauze screen (500–900 Hz; Fig. 2a). This procedure considerably increased the signal to noise ratio for further processing. Then, amplitude discriminator with a threshold of +8 dB above the mean noise level was used to isolate ENTOMOLOGICAL REVIEW Vol. 95 No. 4 2015
Fig. 1. The “artificial animal” device: (1) case; (2) board; (3) heating elements; (4) gauze screen permeated with meat juice; (5) microphone; (6) amplifier; (7) metal plate with thread for attachment to the support; (8) electric connectors.
the peaks reflecting the acoustic activity of mosquitoes, and to record the moments of crossing the threshold (Spike-C3 software, Russia). These peaks marked the starting points of mosquito landings on the screen, their take-offs, and short flights within the screen area. After peak isolation, the sampling rate was reduced to 11.025 kHz in Sound Forge 10, to speed up further processing. Data for the mosquito attack intensity plots were calculated using the Average Plot 2.04 software (Russia). Data processing consisted in counting the acoustic peaks within a 5-min interval. During the subsequent iterations, the interval was shifted by 20 s, and the peak counting was repeated. The results for the overlapping intervals were then averaged. A similar algorithm was earlier proposed for analysis of the temporal structure of neuronal spike patterns (Szücs, 1981). In several special cases, the counting interval was reduced to 1 min to increase the time resolution, and the consecutive shifts were reduced to 4 s. The behavior of mosquitoes on the gauze screen was recorded with a Panasonic NV-GS500 digital video camera (Japan), simultaneously with recording the sounds of attacking mosquitoes. Analysis of the video information allowed us to determine the statistical ratio of the number of attacks and that of amplitude peaks in the acoustic oscillogram. This ratio was close to 1 : 2, i.e., the number of attacks could be determined by halving the value obtained by acoustic data analysis. This relation appears quite feasible since each attack included a landing and a take-off. The inevitable omission of weak signals from mosquitoes
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Fig. 2. A sonogram of a fragment of recording: (a) the range of the second harmonic of the flight sounds of mosquitoes attacking the Device; (b) the frequency track from the light meter output; (c) the range of the first harmonic of the mosquito flight sounds. Abscissa: time, min; ordinate: frequency of harmonic components of the signals, Hz.
Fig. 3. The gauze screen of the Device with attacking mosquitoes.
that flew on the screen periphery as well as the mutual concealment of sounds of several mosquitoes during acoustic analysis was compensated for by the records of short flights within the screen area.
(Fig. 2b), its upward deviation corresponding to an increase in the illumination intensity.
Changes in the illumination level near the Device were visualized by sonograms of the corresponding fragments of acoustic records (Sound Forge 10). The current level was shown in sonograms as a solid line
Female mosquitoes started to attack the gauze screen 10–15 min after switching on the heater. Each mosquito tried to reach the nonexistent host skin surface with its proboscis 7–14 times, after which it either
RESULTS
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moved out of the camera field of view or flew onto a new area within the screen. From 5 to 12 mosquitoes were usually present simultaneously on the screen (Fig. 3). According to the control net-sweeping collections of the mosquitoes attacking the Device, their species composition was typical of Moscow region: Aedes (Ochlerotatus) communis (De Geer, 1776), A. (Och.) diantaeus (Howard, 1913), A. (Och.) punctor (Kirby, 1837), A. (Och.) excrucians (Walker, 1856), A. (Och.) dorsalis (Meigen, 1830), and A. (Och.) riparius (Dyar et Knab, 1907) (identified after Gornostaeva and Danilov, 1999).
Fig. 4. Changes in the intensity of mosquito attacks on the “artificial animal” in the evening hours. The illumination level gradually decreased from 1100 to 430 lx during the observation.
Continuous observations revealed a considerably non-uniform dynamics of mosquito attacks on the bait (Fig. 4). Peaks of mosquito activity alternated with drops with a mean interval of 30 min (20–50 min in different sessions). Quasi-periodic fluctuations of the attack intensity were recorded in all the experiments. Based on these observations, it was assumed that the formation of the first peak could be triggered by the very fact of the Device appearing in the area. However, this hypothesis was not confirmed by statistical tests. No significant correlation was found between the parallel records of mosquito signals from two different Devices. Although the activity peaks in the two record channels sometimes looked coordinated, correlation analysis did not confirm any such coordination; thus, the peaks of attack intensity on two spatially separated Devices were triggered independently. The fluctuations of mosquito attack intensity overlapped with a gradual increase in the evening and a decrease at dawn (Fig. 5), which manifested the general daily dynamics of mosquito activity (Vinogradova and Karpova, 2010). An oscillogram of a fragment of recorded sounds of mosquitoes attacking the Device is shown in Fig. 6a (a sonogram of the same fragment is shown in Fig. 2). Processing of the recorded information by the above method produced the plot of variation of the number of attacks per minute (Fig. 6b). Visual comparison of the two data formats in Fig. 6a and Fig. 6b revealed no obvious correspondence: the areas of the greatest signal amplitude in the oscillogram did not coincide with the maxima of the plot of attack intensity. This difference was related to the fact that when building the plot in Fig. 6b, low-amplitude peaks were counted as effectively as high-amplitude ones. ENTOMOLOGICAL REVIEW Vol. 95 No. 4 2015
Fig. 5. Sample plots of the intensity of mosquito attacks in the morning (a) and evening (b) hours.
Changes in the illumination level within the same time interval are shown in Fig. 6c. The irregularities shown as serrated segments at the peaks were caused by the movements of upper tree branches which periodically shaded the Device during a brief gust of wind. In this and several other special cases, there was a quite definite relation between the illumination level and mosquito activity: an increase in illumination caused an increase in the intensity of mosquito attacks. However, the effect of short-term changes in illumination on the phase and amplitude of the fluctuations of attack intensity could not be statistically confirmed on the entire body of data. When two Devices were used
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screen and their subsequent retreat, could be observed within a time interval of about 10 min. The coordinated rises and drops of activity can be most easily explained by assuming that these processes largely involved the same individuals. At the same time, new mosquitoes which had not participated in the previous cycles of activity could also fly into the experiment area. This fact, in particular, accounted for the trend for increasing attack frequency in the evening hours.
Fig. 6. Synchronous records of the acoustic signals of mosquitoes attacking the “artificial animal” and the illumination level: (a) an oscillogram of a fragment of acoustic recording; (b) a plot of the intensity of mosquito attacks obtained by processing the acoustic signal shown in (a) (the minimum value at the beginning corresponds to 2 attacks per min, the maximum value, to 16 attacks per min); (c) a plot of the illumination level (the minimum value at the beginning is 270 lx, the maximum is 410 lx).
simultaneously, changes in the total illumination did not produce identical responses of mosquitoes on each Device. Analysis of video recordings made simultaneously with acoustic ones revealed some characteristic acoustic patterns which could be used for interpreting the mosquito behavior near the Device. The wingbeat frequency increased abruptly during the take-off; this moment could be easily identified aurally, whereas in the sonograms it produced a ♪-shaped element. The opposite situation was observed during the mosquito landing on the screen: the sound frequency gradually decreased while its amplitude usually increased. The sounds of short flights within the screen area usually contained no fragments with distinct frequency modulation. Based on these observations, we were able to count the landings and take-offs using two audio recording channels, as a means of additional control. DISCUSSION Analysis of our data showed that two opposite processes, namely mass attack of mosquitoes on the Device
Earlier studies of the behavior of mosquito females near the host led to the discovery of the “invitation effect” (Alekseev et al., 1977): the females seeking a host were additionally attracted by those mosquitoes which had already found one. The more females participated in the current attack, the more would be subsequently attracted to the same place. Thus, two groups of mosquitoes: those which have already landed on the host and those flying around it or resting on the nearby vegetation, essentially formed a positive feedback system. However, the signal component involved in information transfer between the two groups remains unknown. In the context of our data, an abrupt increase in the mosquito activity near the Device (Fig. 4) may be explained by positive feedback based on the invitation effect. At the same time, the periodical nature of changes in the attack intensity must be controlled by some other processes. It may be assumed that mosquitoes, having failed to obtain a bloodmeal from the bait, lost interest in it and aggregated on vegetation in the immediate vicinity of the experiment area. Then, 20–50 min later, the memory trace of this experience gradually faded and the mosquitoes returned to the bait. The new cycle could also be triggered by other females which flew to the Device after the end of the previous activity peak. Then the process was repeated due to the invitation effect. However, the same fluctuations of activity were recorded in the morning hours, when the general intensity of mosquito attacks gradually decreased (Fig. 5a). Considering these observations, it may be concluded that the period of quasi-periodic rises and drops of intensity of mosquito attacks on the Device was largely determined by some endogenous factors. A process involving positive feedback is unstable and should be affected even by minor disturbances, such as local changes in illumination in partly cloudy weather. The effectiveness of such factors considerably depends on their coordination with the phase of ENTOMOLOGICAL REVIEW Vol. 95 No. 4 2015
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mosquito activity. For example, the minimal sensitivity to external influences can be expected at the peak and during the subsequent decline of activity, and the maximal sensitivity, during the period directly preceding a peak. In the latter case, external destabilizing factors could trigger a new rise in activity, thus shortening the self-oscillation period. The variable sensitivity to external influences may account for the inconsistency of our data, which demonstrated a distinct response of mosquitoes to increasing illumination in some periods (Fig. 6), whereas in other time intervals no such response could be statistically confirmed. In view of our results of continuous monitoring of the intensity of mosquito attacks on the imitated host, some questions can be raised. For example, it is unknown how the absence of an actual bloodmeal affects the behavior of mosquitoes attacking the bait. The unavailability of blood is an essential trait of the “artificial animal,” but it is also largely characteristic of a human in protective clothing. It also remains unknown how the dynamics of mosquito attacks depends on the size of the host. It may be assumed that a large group of insects gathered around a large mammal would have a higher persistence and, therefore, a greater period of spontaneous fluctuations of attack intensity. In addition, certain stratification may occur. For example, according to Popov (1953), females of Aedes cinerius Meig. do not fly higher than 50 cm above the soil surface, whereas Ae. excrucians Walk. tend to attack the upper body of man. Differences in the behavior of different mosquito species near the bait should blur the resulting picture. On the other hand, since the periodic fluctuations of the total activity were quite distinct, it may be concluded that species-specific behavioral traits did not considerably affect the results of our experiments. According to Detinova and co-authors (1978), 30–40 ind. captured on an exposed shin in 5 min corresponded to low activity of mosquitoes. Therefore, the mean activity of mosquitoes in the forests near Moscow may be characterized by a value 2–3 times as great, i.e., about 100 attacks per 5 min. We recorded about 40 attacks on the Device per 5 min (Figs. 4, 5), i.e., about 2.5 times less. However, since the surface area of a human shin is at least an order of magnitude greater than that of the gauze screen of the Device, the bait efficiency in our experiments was quite satisfactory. It should also be noted that when the human landing catches method is used, mosquitoes are attracted ENTOMOLOGICAL REVIEW Vol. 95 No. 4 2015
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not only by the exposed shin but by the entire human body. When comparing the potential bait efficiency of the Device and experimental animals, it should be borne in mind that even conspecific animals vary in their odor complexes depending on sex, age, physiological state, etc. In addition, placing of an animal into the experimental setup would most probably be stressful for it. The variable odor parameters of the animals may hinder the control experiments and interpretation of the results obtained. In contrast, the gauze screen of the Device can be permeated with any combination of biological materials or their synthetic analogs, and the attractive properties of compounds or mixtures can then be tested in free-choice experiments with two Devices. Thus, our Device can be used for standardized assessment of efficiency of chemical attractants and repellents. Under the natural conditions, our technique allows the effects of short-term natural factors on mosquito activity to be estimated. Until this research, there has been no data on rapid changes (with a typical rise and drop time of about 10 min) of mosquito activity near the bait. Already the first experiments showed that the intensity of mosquito attacks under the natural conditions was not only highly variable but quasi-periodic. In view of these results, the possibility of such fluctuations should be taken into account when studying the effects of various factors on mosquito behavior. REFERENCES 1. Alekseev, A.N., Rasnitsyn, S.P., and Vitlin, L.M., “On the Group Behavior of Females of Bloodsucking Mosquitoes (Diptera, Culicidae, Aedes): Observations of the Invitation Effect,” Med. Parazitol. Parazitar. Bolezni 46 (1), 23–24 (1977). 2. Aschoff, J., Biological Rhythms, Vol. 1 (Plenum, 1981; Mir, Moscow, 1984) [in Russian]. 3. Barashkova, A.I. and Reshetnikov, A.D., “Ecology of Bloodsucking Mosquitoes in the Central Taiga Zone of Yakutia,” Izv. Samar. Nauchn. Tsentra Ross. Akad. Nauk 14 (5), 143–144 (2012). 4. Barrozo, R.B., Schilman, P.E., Minoli, S.A., and Lazzari, C.R., “Daily Rhythms in Disease-Vector Insects,” Biol. Rhythm Res. 35 (1/2), 79–92 (2004). 5. Bezzhonova, O.V., Ivanitskii, A.V., and Fedorova, M.V., “Nocturnal Activity of Mosquitoes (Diptera, Culicidae) in Volgograd and Its Environs,” Med. Parazitol. Parazitar. Bolezni, No. 4, 25–27 (2004).
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