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Physical and biological effects on moths’ navigation performance

Movement Ecology volume 13, Article number: 17 (2025) Cite this article

Abstract

In a chemosensing system, the local olfactory environment experienced by a foraging organism is defined as an odorscape. Using the nocturnal pink bollworm moth (Pectinophora gossypiella), we tested the combined effect of three biophysical aspects in its immediate odorscape to shed light on the coupling effects of biotic and abiotic factors on navigation performances of a nocturnal forager: i) the quality of the pheromone source, ii) the pheromone availability, and iii) the airflow characteristics. The navigation performance of the males was investigated using a wind tunnel assay equipped with 3D infrared high-speed cameras. The navigation performance of the males was analyzed using ethological and biomechanical parameters.

The results of this work indicate that: (1) the biophysical factors have combined effects on the navigation performance of mate-searching males; (2) Natural and sexual selection play an important role in shaping the pheromone-mediated sensory performance of nocturnal male moths; herein, the role of natural selection overrides that of sexual selection; (3) During odor-mediated mate-finding navigation, the male moth applies a tradeoff decision-making process based on weighted information from the biological and physical characteristics of the odorscape. This decision-making process includes weighting the tradeoff between the cost involved in flying under different flow conditions, the availability of different odor sources, and their quality.

Introduction

Chemical-mediated communication is the most common sensory modality adopted by organisms for survival and reproduction [33]. Evolutionary forces of natural and sexual selection have shaped an array of sensory adaptations [17, 18] that are required to accomplish various chemosensory fitness-related behaviors [14], such as finding prey [1], avoiding predators [24], territory marking [51], host finding [58], and mate localization [22]. The ability of an organism to locate a chemical source is considered one of the most complicated behavioral tasks due to the fluctuating and chaotic conditions prevailing in natural environments [5, 49]. Chemosensing is specifically challenging in aerial systems, which are characterized by relatively low density, high dynamic viscosity, and highly fluctuating chemosensory environment [47, 61]. Much interest in the field of behavioral ecology and sensory ecology has been dedicated to understanding the sensory adaptations and sensory performance (i.e., locomotion) of airborne chemosensing navigators [17], Riffel et al. [47, 60]. The chemical environment or the olfactory landscape [52] experienced by the foraging organism is conceptualized as an odorscape [64].

Moths are widely used as animal models in the field of chemosensing sensory performance. Moths (Lepidoptera) are acknowledged as a paragon of odor-mediated mate-searching [6, 7]. In moths, mate finding is mediated by long-range chemosexual communication, mostly with females sending the signal and males as receivers [64]. Male moths locate their conspecific mates by sensing pheromone molecules emitted by females as they fly upwind. During mate finding, male moths may experience a wide range of odorscapes due to the fluctuating nature of their immediate environment [5, 49]. The properties of the specific odorscape are governed by abiotic and biotic factors,among the abiotic factors are wind speed, turbulence level, and air temperature [47, 56], while the biotic factors may consist of odors of prey, host plants and potential mates [13, 37]‏). Evolutionarily, chemo-sexual communication in moths constitutes an interesting case study as it is channeled via pheromone signaling shaped by the involvement of both natural [4, 14] and sexual selection [27, 29, 53]. Yet, the evolutionary processes that shape male mate-searching behavior in a complex odorscape are still obscure [7, 66].

Given the complexity and variability of odorscapes in natural surroundings, the study of mate-searching in male moths has been conducted in a controlled environment (e.g., wind tunnel assay). So far, most empirical studies have focused on the effect of a single factor only [7, 8]. For example, previous studies have shown the specific effect of a physical factor such as the current wind speed [42], turbulent level [41], the structure of the pheromone plume [63], the pheromone concentration [20] and ambient temperature [9]. Other studies have shown the specific effect of a biological factor, including the availability of potential mates [2], the reproductive potential of the available females, projected from their emitted pheromone characteristics [26], and the navigating male’s body size [34]. Yet, studies examining the combined effects of various odorscape factors on the male moths’ navigation are scarce [7].

Evidence, for the combined effect of different factors on the mate-searching behavior of male moths has been shown, including the interplay between light and airflow [8] and the interplay between the availability of potential mates and their reproductive potential [25].

Here, we aimed to elucidate the navigation behavior of mate-searching male moths under different odorscapes. The various odorscapes in this study are defined by the combinations of three biophysical factors: (i) the quality of the odor source, (ii) the availability of one or two odor sources, and (iii) the flow condition, using the pink bollworm moth (Pectinophora gossypiella) as a model species. The experiments were executed using wind tunnel assays, and the navigation performances of males were analyzed. From an eco-evolutionary standpoint, the roles of natural and sexual selection in shaping traits have been extensively debated (West-Eberhard 1983; Clutton-Brock 2004; Shuker 2010). To provide clarity, we adopt Greenfield’s [27] framework, which conceptualizes sexual selection as a subset of natural selection. Additionally, we utilize Endler’s [17] ‘sensory drive hypothesis,’ emphasizing the dynamic interaction of environmental biophysics, sensory systems, and sender-receiver communication in shaping chemosensory evolution through ecological and evolutionary forces.

Materials and methods

General

The pink bollworm moths were reared under laboratory-controlled conditions at 25–27 °C, 60% RH, and 14:10 h L:D, at the Department of Entomology, The Volcani Center, Israel. The larvae were fed on premixed food (38‐0600; Ward’s Science, Rochester, NY). Virgin adults were obtained by separating males and females at the penultimate larval stage using the black spot on the males’ 6th abdominal segment, which indicates the presence of testicles (Dou et al. 2019). Newly emerged adult males or females were placed separately in screen cages (0.2 m × 0.2 m × 0.2 m) and fed 10% sugar solution ad libitum. Three-day-old virgin males and females were used in all experiments.

The wind tunnel apparatus

The wind tunnel (1 × 1 m2 cross section and 3m long) is placed in a dark room with a control condition at 25 °C and 60% RH. The wind speed, set to 0.25 m/sec, is kept steady using sets of stainless-steel meshed screens at both the inlet and outlet ends of the tunnel. The tunnel is equipped with a built-in tracking system (Scope visual platform model Luteus-1300M-L) and an array of infrared (IR) lights, outside the visible spectrum of moths. Two active-pixel sensor cameras (CMOS) located in stereoscopic viewing mode generated a three-dimensional image field (1.0 m × 1.0 m × 2.0 m) capturing the tunnel volume from the males’ release point to their landing point on the odor source. The system tracked and digitized the three-dimensional position (x, y, z) of the flying moths (body length: \(\overline{\text{x} }\)=0.012 m; wingspan: \(\overline{\text{x} }\)=0.02 m) at a frequency of 75 Hz. Trajectory data of successful flights (males that reached the odor source in a continuous flight) were processed through a ‘Data-Processing Pipeline’ of a series of two data steps: (i) Quality assessment and (ii) Spatial calibration (see ‘Data-Processing Pipeline’ in "Supplementary" for detailed description).

The biophysical factors defining the odorscapes

I) The quality of the odor source

Pink bollworm males can distinguish between females with high and low reproductive potential by their pheromone characteristics [25, 26]. The reproductive potential of insects is strongly affected by nutrition [36, 59, 65], for pink bollworm female moths, see [26]. To achieve distinct differences in their reproductive potential, females were divided into two diet-based groups on the day of adult emergence: 1) Females with high reproductive potential were fed on 10% sugar solution ad libitum (henceforth: fed females), 2) Female with low reproductive potential received tap water (henceforth: starved females). Females in the two groups were placed in different screen cages (30 cm3) in the same climatic room.

ii) The availability of one or two odor sources

Three-day-old adult virgin moths were obtained from the rearing room approximately 30 min. before the onset of their sexual activities. Generally, while females calling periods are intermittent, the specific timing and duration of this calling behavior differ across individuals in the population [31, 35]. Therefore, to maximize the likelihood of female calling during the experiment, four pink bollworm females, fed or starved, were used as the pheromone source, following the protocol of Gonzalez-Karlsson et al. [26]. The females, fed or starved, were placed in a small horizontal cylindrical screen cage (0.02 m dia. × 0.03 m). In the no-choice experiments, males were presented with one cage of either four fed or four starved females, whereas in the choice experiments, males were presented simultaneously with two cages, one holding four fed females and the second enclosed with four starved females.

iii) The characteristics of the flow

To test the effect of the wind flow on the male moth’s flight trajectory, two flow characteristics were defined: undisturbed and disturbed. Undisturbed, relatively steady flow is generally maintained in the wind tunnel due to the meshed screens at the tunnel’s inlet (henceforth: an undisturbed flow).

In order to disturb the flow downstream of the wind tunnel, we placed a vertical cylinder (0.05 m in diameter and 1.0 m high) 0.2 m upstream behind one odor source (assuring that the odor source was out of the recirculation region of the cylinder’s lee side and placed in the near wake region). As a result, the disturbed flow was characterized by repeating patterns of swirling vortices downwind from the cylinder, similar to a von-Kármán vortex street (Fig. 1A). The main advantage of this practice is the phase locking of the vortices. This practice has been commonly used in empirical studies on odor source localization [8, 23]. The flow-disrupting cylinder was placed either upwind of the odor released by fed or starved females.

Fig. 1
figure 1

Experimental bioassay. A A schematic illustration of the wind tunnel experiments in a choice assay between two different odor sources; Left: Undisturbed flow, Right: Disturbed flow. The vertical cylinder is placed 0.2 m upwind of one odor source. Blue and red represent the emitted plumes of different source quality, B the trajectory segmentation: an example of a 3D trajectory (teal circles), each segment connecting two consecutive positions. The straight white line depicts the distance. An inset showing the triangle of velocities of one segment. A segment is represented by the ‘track’ vector (grey). Each segment has a duration of \(\Delta t=0.013\) sec

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This experimental setup allowed testing the combined effects of the availability of choice (no-choice or choice), the quality of the signaler (fed or starved females), and the flow characteristics (undisturbed or disturbed) simultaneously in one bioassay.

Wind tunnel assay

The navigation performances of male moths were tested in an array of wind tunnel assays (Fig. 1A) at the peak of calling time, 4-5 h after the onset of the scotophase, at 25–27 °C, and 14:10 L:D. The screen cage, enclosing either fed or starved females, was tied to a thin stick (height: 0.7 m, diameter: 0.02 m) located 0.2 m downwind from the upwind end of the tunnel at the height midpoint (0.5 m) and 0.45 m laterally with respect to the proximate side wall (right or left). During the experiments, the flying males were provided with either a choice between two sources of female-emitting pheromones or no-choice, whereby only one source of odor was provided to the mate-searching males. In the choice treatments, the two odor sources were placed 0.1m apart (See Fig. 1A). The positions of the two odor cages alongside the vertical cylinder (in the treatments that included the effect of disturbed flow) were exchanged every five runs to avoid directional bias in male flights. Males were randomly taken individually from the male cage and released at the downstream releasing midpoint, 2.0m downstream of the odor source cages. Each male was free to take off at will. Males that did not take off within 1 min. or did not reach the source in a continuous flight were excluded from further analyses. Each male’s flight was recorded once.

Data-processing methodology

Data reduction—the trajectory data of successful flights were processed through two data steps (see ‘Data-Processing Pipeline’ in “Supplementary” for detailed description): (i) Quality assessment: the analytical method of Statistical Outlier Removal for noise filtering (SOR) in CloudCompare (version 2.12, GPL software for 3D point cloud processing, 11) was used to exclude navigations with noise levels > 15%; and (ii) Spatial calibration: a computational procedure that flipped (if necessary) the horizontal axis to assure that all flight trajectories are aligned.

Flight trajectory segmentation—we applied a path segmentation method [15] for each successful flight, which converted the flight trajectory into a sequence of three-dimensional linear segments, where each segment (vector) is the connecting linear line between sequential positions (see the example in Fig. 1B). These sequences are based on discretization of the wind tunnel domain into imaginary cells (along the longitudinal plane: 400 cells, cell size: 0.05m × 0.1m) and the along the transverse plane: 400 cells, cell size: 0.05 m × 0.05 m) and projecting them on the imaginary cells’ domain. The cell size was set to a minimum of one order of magnitude, larger than the average net displacement of the moth’s position between sequential frames (X: 0.005 m; Y: 0.003 m; Z: 0.005 m). The path segmentation algorithm was validated by comparing its performance against ground truth observations, ensuring the reliability and accuracy of the segmentation process..

The combination of the three biophysical factors: (i) the quality of the odor source: fed or starved females, (ii) the availability of odor sources: one or two, and (iii) the flow condition: undisturbed or disturbed, was accumulated to nine treatments (4 no-choice and 5 allowing a choice) resulted in 14 combinations (one in each of the four no-choice treatments and 2 for each of the choice treatments) (see the experiments’ matrix in Table 1).

Table 1 The experimental array of combinations of the three biophysical aspects: i) the availability of one (no-choice) or two (choice) odor sources. ii) the flow condition: either Undisturbed- no cylinder is placed in the wind tunnel, or disturbed- a cylinder is placed 0.2 m upwind of the odor source (see Fig. 1A)
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Among the five choice treatments listed in Table 1 (T5-9), in one (T5) the flow was undisturbed, while the other four (T6-9) experienced disrupted flow. In these four treatments, the two sources were characterized by different levels of physical disturbance: the odor source that was directly affected by the vertical cylinder behind it was termed ‘Aligned’; i.e., placed at the centerline of the von-Karman street, while the neighbor odor source was termed ‘Offset’; i.e., placed off the von-Karman street, experiencing higher shear values compared to the former case. The effect of the flow conditions on the male choice of odor source (fed females or starved females) was tested in treatments T8 and T9, while the effect of the flow conditions on the male choice of similar odor source (T6 and T7) served as a control (Table 1).

Data analyses

Parameters

For the analyses of the males’ navigating performances, three behavioral characteristics were defined: (1) The success rate in locating an odor source; the ratio (%) of males who have reached any odor source out of all participating males in the treatment, (2) Male preference; the proportion of males in a choice treatment, that picked each odor source, and (3) Navigation pattern; the trajectory data of successful navigations were quantified using spatiotemporal parameters. The Navigation pattern was characterized using three parameters: navigation efficiency, total navigation time and navigation speed. The Navigation efficiency was defined as the ratio between the measured navigation distance and the direct flight distance to the odor source. Lower values indicate higher navigation efficiency. Navigation time corresponds to the elapsed time (sec) from the moth takeoff to landing. Navigation speed was calculated for each segment of the flight trajectory.

Statistical analysis

The analysis of the ‘success rate’ (1) in all 14 combinations was performed by comparing the success rate among all treatments using a Two-sided Fisher exact test for multiple comparisons (α = 5%), followed by the post hoc comparison of Holm-Bonferroni sequential procedure. The analysis of ‘male preference’ was conducted for each of the five choice treatments. We tested whether the male’s preference for each treatment significantly differed from 50% (1:1 hypothesized ratio), using G-test goodness of fit (α = 5%, DF = 1). Unless stated otherwise, outliers were identified using the K-nearest neighbor method. The analysis of the Navigation pattern was based on the trajectory data from the two sets of trajectory data superimposed on the planes: longitudinal and transversal, thus generating two population-level count matrices for each of the 14 combinations. A comparison of the two parameters: navigation efficiency and total navigation time, among all combinations, was made using the non-parametric one-way Kruskal–Wallis H-test, followed by Wilcoxon post hoc comparison. A population-level analysis of the moths’ speeds was performed using a one-way mixed-model ANOVA with individuality modified as a random effect, followed by the Tukey HSD post hoc test. Statistical assumptions of homogeneity of variance for multiple comparisons (Levene’s test), normality (Shapiro–Wilk W-test), and sphericity (Mauchly’s test) were checked. Violation of normality and homogeneity of variance were corrected using a Box–Cox transformation. Finally, a correlation between navigation efficiency and total navigation time was done using Spearman’s rho (ρ) rank-order correlation test. Outliers were identified using the Mahalanobis distances method.

Results

Navigation performance

The results provide strong evidence for the combined effects of the three bio-physical aspects on the male moths’ flight performance (Fig. 2). First, the effect of the physical factor (the wind conditions), was demonstrated. The lowest success rates in landing on an odor source were obtained in the presence of the disturbed flow (T3-4, 6–9). In particular, the success rate of males navigating under disturbed flow in the no-choice treatments (T3-4) was significantly lower compared with all other combinations (p < αAdjusted). Second, the two biological factors: i) the quality of the odor source and ii) the availability of one or two odor sources, also strongly influenced the success rate of males. When the odor of high-quality females was presented to males in choice or no-choice treatments, the success rate of males reaching this odor source was significantly higher. More males eventually landed on the odor source of high-quality females vs. low-quality females. In the absence of disturbance, the success rate of males navigating to the odor source of high-quality females was significantly higher than that of males navigating to low-quality odor in no-choice (T1-T2) and choice (T5) treatments. The advantage of the high-quality odor was lost when the flow was disturbed upwind of the high-quality odor source (T3, T6, T9). Apparently, the disturbed flow significantly reduced the success rate of navigating males regardless of the odor quality (T3-4, T6-9).

Fig. 2
figure 2

Success rate of navigating males in the wind tunnel bioassays involving combinations of three biophysical factors: the flow (undisturbed or disturbed), the quality of the females emitting the odor (high or low), and the availability of odors (no-choice and choice). x-axis: The treatment (denoted by ‘T’), different combinations of the flow characteristics, the odor quality, and the availability of odor sources. y-axis: % of successful males (among all participating males) reaching an odor source. The vertical cylinder denotes the in-line disturbed flow 0.2 m upwind of the odor source, and its absence denotes the Offset source. In the choice treatments, the males’ success rate in locating the two sources is shown as stacked bars. The success rate (%) of all 14 combinations was compared using the two-sided Fisher exact test for multiple comparisons (α = 5%) and post hoc comparison of Holm’s sequential Bonferroni procedure. Different letters indicate statistically significant differences at the adjusted Holm’s-Bonferroni p-values. In each of the five-choice treatments, a within-comparison between the two odors was done using G-test goodness of fit (α = 5%, DF = 1). **, ***, and **** indicate statistical significance at 0.01, 0.001, and 0.0001, correspondingly

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Interestingly, when the odor of high-quality females was presented to males, in all choice treatments, the success rate of males reaching any odor source (T5, T6, T8, T9) was significantly higher than when only the odor of low-quality females was presented (T7), suggesting higher motivation of males to reach an odor source when the odor of high-quality females was detected (Fig. 2). Examples of unsuccessful and successful navigation trajectories are shown in Fig. 3.

Fig. 3
figure 3

Trajectories of stereotypical navigations. (A and B) Unsuccessful flights towards a high-quality source. (C–H) Successful flights. C A no-choice treatment, reaching a high-quality source. (D and E) Choice treatments; choosing the high-quality source (D) or the low-quality source (E). (F and G) Sources of different qualities: Choosing the Offset (indirectly disturbed), low-quality source (F), or the in-line (directly disturbed) high-quality source (G). (H) Sources of similar quality (both high), choosing the in-line odor source. The purple line represents the projection of the central bee-line

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Navigation patterns: population-level

The biophysical conditions had a significant effect on the speeds of the navigating male moths (one-way mixed-model ANOVA with random effect, F13 = 82.28, p < 0.0001) (Fig. 4A). Navigations under disturbed flow conditions (Fig. 4A, T3, 4, 6–9) were characterized by higher moths’ speeds and a higher degree of dispersion than navigations in undisturbed flow (Fig. 4A, T1, 2, 5) (disturbed flow: median’s range, 0.56–0.67 m/sec; undisturbed flow: median’s range, 0.52–0.55 m/sec) (Fig. 4A, see also Fig. 4B for clear tendencies). In particular interest was the higher speed of moths that reached the in-line, directly disturbed odor source than the speed of moths in the same choice treatments who reached the off-line, indirectly disturbed odor sources (T6-9) (p < αAdjusted). This phenomenon occurred regardless of the odor quality, thus corroborating the strong effect of the physical factor. The effect of biological factors on the moths’ speed was demonstrated under steady flow conditions (Fig. 4, T1, 2, 5). When given a choice, in a steady flow, males who navigated to the higher odor source quality navigated significantly faster than males who reached the lower quality odor (Fig. 4, T5 (p < αAdjusted). In the absence of choice, when the odor of high-quality females or that of low-quality females were given alone, the navigated males’ speed did not differ (T1-2) (p < αAdjusted), suggesting the strength of the biological factor under conditions of steady flow.

Fig. 4
figure 4

The speed of males navigating to odors in the 14 options among 9 treatments. A vertical cylinder denotes the identity of the in-line (directly disturbed) odor source placed downwind from the cylinder. The vertical dashed line separates the two odor sources in each choice treatment. A. y-axis: male speed. One-way mixed-model ANOVA with random effect (male identity) followed by Wilcoxon post hoc comparison and Holm-Bonferroni sequential procedure were used to compare among means of all 14 treatments. Different letters indicate statistically significant differences after the adjusted Holm’s-Bonferroni p-values. B Grand mean (average of all means) ± SD of all means. Horizontal dashed lines (in 4A) represent the 25th (lower) quartile, the 75th quartile (upper), and the median (intermediate)

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Navigation patterns: individual level

In addition to the above population-level analysis, an individual-level analysis was performed using the parameters of navigation efficiency (Fig. 5A) and total navigation time (sec) (Fig. 5B). A significant effect of the biophysical conditions on the two parameters was demonstrated (One-way Kruskal–Wallis: navigation efficiency, H13 = 249.63, p < 0.0001; total navigation time, H13 = 93.97, p < 0.0001). The results of the navigation efficiency followed the trend observed in the airspeed analysis, with lower efficiency (i.e. lower value) when navigating to the in-line disrupted odor source (Fig. 5, T3-4, 6–9), thus supporting the predominant effect of the physical factor. Here again, in choice treatments, lower navigation efficiency and higher navigation time values were obtained for the in-line disturbed odor regardless of the odor quality (T6-9). The lowest values of navigation efficiency and highest total navigation time were obtained when males navigated to disturbed odors in no-choice treatments (T3-4) (\(\overline{\text{x}}\) ± SEM: Navigation efficiency, high quality, 8.644 ± 0.446; low quality, 8.581 ± 0.639; total navigation time, 22.73 ± 2.10; low-quality source, 21.11 ± 1.31 s, Wilcoxon post hoc method corrected by Holm-Bonferroni sequential procedure, in both p < αAdjusted) (Fig. 5A). The highest navigation efficiency was observed under undisturbed flow in no-choice and choice treatments (Fig. 5, T1-2, 5). These treatments demonstrated the combined effect of the source quality and its availability on navigation efficiency and navigation time. Here again, in the choice treatment (T5), males who chose the higher-quality source exhibited higher navigation efficiency than males who navigated to low-quality odor.

Fig. 5
figure 5

Individual-level analysis for successful navigations. A. Navigation efficiency (\(\overline{\text{x}}\) ± SEM). for all 14 treatments. B. Navigation time (\(\overline{\text{x}}\) ± SEM) for all 14 treatments. The dashed line separates the no-choice treatments from the choice treatments. In both A and B, x-axis: treatment, and y-axis: (\(\overline{x}\)+ SEM). A vertical cylinder denotes the identity of the in-line (directly disturbed) odor source placed downwind from the cylinder. One-way Kruskal–Wallis H test followed by Wilcoxon post-hoc comparisons were used to compare all treatments. Different letters indicate statistically significant differences at p-value < 0.05

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Discussion

The chemosexual system of moths is comprised of a foraging male which navigates in a complex odorscape of its species-specific sex pheromone dictated by abiotic and biotic factors. Due to the methodological complexity of this system, most empirical studies have tested the effect of a single factor on the pheromone-mediated navigation performance of male moths [7, 8]. In this study, we suggested to bridge this gap by selecting multiple biophysical factors: (i) the nature of the flow, (ii) the availability of odor sources, and (iii) the quality of the odor sources. The results of this study provide evidence for the combined and relative effects of the biological and physical variables encompassing the odorscape of the chemosensory performance of male moths. The results shed light on two major selection pressures: natural and sexual, that play an important role in shaping the pheromone-mediated sensory performance of mate-finding in a nocturnal male moth, with the dominant role of natural selection. The insights obtained in this paper provide important knowledge in elucidating the complex study of chemosensation, specifically, in aerial ecosystems.

Effects of the physical characteristics

The nature of the flow in the male moths’ odorscape had a stronger effect on the navigation performance than the odorscape’s biological characteristics. The effect of the flow was demonstrated in different parameters of the navigation performance: the source localization (Fig. 3) and the navigation pattern (Fig. 4–5). In an odorscape consisting of a single disturbed odor source, the success rate (%) of source localization of flying males was low (ca. 12–18%), regardless of the quality of the pheromone-emitting females in the odor source (T3 and 4). In choice experiments, the strong effect of the flow was further demonstrated with the significant preference of males for the Offset, indirectly disturbed source over the in-line, directly disturbed source (T6-9), regardless of the odor characteristics. Furthermore, the navigation patterns under a disturbed flow differed significantly from those under an undisturbed flow. Navigations in disturbed flow were characterized by increased variability (Figs. 4 and 5) and higher speeds (Fig. 4). Similar observations were reported by Cardé and Knols [8] for the gypsy moth (Lymantria dispar).

Navigating through a disturbed flow requires higher energy expenditure than navigating in an undisturbed flow due to higher metabolic demands [57]. In an ecological context, the odor-mediated navigation of male moths is a chemosensory fitness-related behavior [14, 17, 52]. Hence, only fit males can successfully navigate to calling females in an erratic environment. The results suggest that male moths experience intense natural selection pressure while searching for a mate [29, 38, 53]. In their natural habitat, nocturnal moths may experience non-optimal odorscapes of disturbed flow [21, 67]. Male moths that have successfully navigated to calling females in an unstable airflow are promoted through natural selection. These results are in line with other studies that showed the prominent effect of disturbed flow on the fluid-dynamic performance of source localization in crabs [48, 62] and different flying animals, including orchid bees, Bombus impatiens [12, 46], hawkmoth, Manduca sexta [44] and Anna’s hummingbird, Calypte anna (Ortega-Jimenez et al. 2015).

Effects of the biological factors

Despite the strong effect of the flow characteristic on the success rate in localizing the odor source, the effect of the odor quality was significant, with a lower success rate (ca. -16%) when only a low-quality odor source was present in the wind tunnel, regardless of the flow characteristics (Table 1). Strong biological effects were expressed in an odorscape characterized by an undisturbed flow. The female reproductive potential, reflected in her pheromone characteristics [26], significantly affected the success rate in source localization of males in the absence of disturbed flow (Fig. 3, T1 and 2). This finding is in agreement with previous studies that demonstrated the role of sexual selection in chemosexual communication in moths [31],Gonzales-Karlsson et al. 2021; [25, 45]. The effect of the source availability (the absence or presence of choice) combined with that of the source quality was shown in the navigational pattern of males in an undisturbed odorscape (T1, 2, 5). In particular, while the source quality did not affect the moths’ navigation pattern (Figs. 4 and 5) under no-choice conditions, it had a significant effect in the choice experiments when two sources were introduced concurrently. Interestingly, the navigation efficiency was lower for males who chose the higher quality source, and they navigated for a longer time. Similar results were obtained by Golov et al. [25], who suggested a tradeoff between the accuracy of the choice and the navigation efficacy.

The combined effect of the biophysical factors

The navigation performance of male moths in complex odorscapes integrates the effect of the disturbed flow, the quality of the odor, and the availability of one or two odor sources. When the two odor sources differed in their quality (T8, 9), males’ preference for the indirectly disturbed source was higher when the released odor was of high-quality females (ca. 80%, T8) than that of low-quality females (ca.65% (T9) (Fig. 2). The movement patterns also provide evidence for the integrated bio-physical effect on the navigation performance of male moths. Interestingly, a comparison of the navigation patterns between the indirectly and the directly disturbed sources (T6-9) revealed that when the two sources were of the same quality (T6, 7), their navigation efficiency and navigation time (Fig. 5) differed significantly with higher efficiency and lower navigation time of the indirectly disturbed source, but when the two odor sources differ (T8, 9) the two tested parameters did not differ significantly between the indirect and the direct disrupted odor sources. These findings demonstrate the mixed effects of the flow characteristics, the source availability, and the odor quality on the movement pattern of odor-mediated mate searching in male moths. Our results add the biotic effect and corroborate Cardé and Knols’ [8] study, demonstrating the physical effect of the flow characteristics and light intensity on the odor-mediated navigation pattern of male moths.

The role of selection forces in shaping the odor-mediated navigation performance of male moths

Chemosensory fitness-related behaviors are assumed to be an adaptive array of sensory modalities shaped by the dual forces of natural and sexual selection [18], Boughman 2002; [14, 52], with natural selection is presumed to be the dominant force [17, 66]. Likewise, the intense pressure of natural selection shapes navigational attributes related ($among others) to the ability of males to successfully performed plume source localization in dynamically changing physical conditions [4, 56], Riffell et al. 2007; &; while sexual selection operates (among others) on the male’s mate choice [25, 26, 31]. As in any fitness-related behavior, the influence of natural and sexual selection is expected to result in in-flight decision-making considering costs and rewards [4, 10].

Our findings emphasize the interplay of sexual and natural selection in shaping the male moth’s navigation when searching for a mate. When available females are limited, the choice of mate is restricted. At times of undisturbed flow, the decision-making process is focused on successfully locating the female emitting the species-specific pheromone (natural selection, see [8, 28]), considering a threshold for the pheromone quality that reflects the female reproductive potential (sexual selection, See [26]). The presence of such a threshold is evident from the lower number of males that successfully localized the odor source emitted by low-quality females (Fig. 2, T1-2). In such scenarios, where the plume dispersion is approximately Gaussian [21], and competing odors are limited, the airborne sampling effort, as verified in the male’s airspeed (Fig. 4), its higher navigation efficiency and reduced navigation time (Fig. 5), and the benefit out of high reproductive potential is increased.

Decision-making tradeoffs are more intricate in complex environments when the competing odor sources vary in quality. Interestingly, the navigation patterns of moths that chose the higher-quality odor differed significantly from the patterns of moths that chose a low-quality odor source (Fig. 4). This work further corroborates Golov et al. [25] approach, as males who chose the high-quality odor source navigated over a wider area for a longer time and course. A recurrent sampling of the two odors following repeated decision-making may take a toll, affecting the decision-making tradeoff and the navigation performance toward each of the odor sources accordingly [25], and a more challenging search mechanism may be required [3, 4].

The interplay between natural and sexual selection has been previously reported for different features of sexual communication, including morphological traits in sea snakes [50] and moths [34], and the effect of predation on frogs [55], field crickets [19], copepods [39], and moths [16].

The findings presented in this study yield several new insights. First, separating the effects of the physical and the biological components in the male moth odorscape on the navigation performance of mate-locating male moths. Second, defining the roles of natural and sexual selection in the pheromone-mediated navigation undertaken by male moths. Notably, the influence of natural selection on the male moth’s navigation performance in a chemosexual odorscape precedes that of sexual selection. Third, within the context of odor-triggered mate localization, male moths engage in a deliberative process of decision-making that involves a tradeoff, assimilating information derived from the biological and the physical attributes of the odorscape: the expenditure associated with flights across diverse flow conditions, the availability of different odor sources, and their potential revenues.

Availability of data and materials

Descriptive data used in this papert is available at https://data.mendeley.com/datasets/k39xx7hngn/1 with DOI: 10.17632/k39xx7hngn.1.

References

  1. Afsheen S, Wang X, Li R, Zhu CS, Lou YG. Differential attraction of parasitoids in relation to specificity of kairomones from herbivores and their by-products. Insect Sci. 2008;15(5):381–97.

    Article  Google Scholar 

  2. Andersson P, Löfstedt C, Hambäck PA. How insects sense olfactory patches–the spatial scaling of olfactory information. Oikos. 2013;122(7):1009–16.

    Article  Google Scholar 

  3. Bartumeus F, Catalan J. Optimal search behavior and classic foraging theory. J Phys A: Math Theor. 2009;42(43): 434002.

    Article  Google Scholar 

  4. Bell WJ. Searching behavior patterns in insects. Annu Rev Entomol. 1990;35(1):447–67.

    Article  Google Scholar 

  5. Bro-Jørgensen J. Dynamics of multiple signalling systems: animal communication in a world in flux. Trends Ecol Evol. 2010;25(5):292–300.

    Article  PubMed  Google Scholar 

  6. Cardé RT. Moth navigation along pheromone plumes. In: Allison JD, Cardé RT, editors. Pheromone communication in moths: evolution, behavior, and application. CA: University of California Press; 2016. p. 173–89.

    Google Scholar 

  7. Cardé RT. Navigation along windborne plumes of pheromone and resource-linked odors. Annu Rev Entomol. 2021;66:317–36.

    Article  PubMed  Google Scholar 

  8. Cardé RT, Knols BGJ. Effects of light levels and plume structure on the orientation manoeuvres of male gypsy moths flying along pheromone plumes. Physiol Entomol. 2000;25(2):141–50.

    Article  Google Scholar 

  9. Charlton RE, Kanno H, Collins RD, Carde RT. Influence of pheromone concentration and ambient temperature on flight of the gypsy moth, Lymantria dispar (L), in a sustained-flight wind tunnel. Physiol Entomol. 1993;18(4):349–62.

    Article  CAS  Google Scholar 

  10. Chittka L, Skorupski P, Raine NE. Speed–accuracy tradeoffs in animal decision making. Trends Ecol Evol. 2009;24(7):400–7.

    Article  PubMed  Google Scholar 

  11. CloudCompare (version 2.12) [GPL software]. 2022. Retrieved from http://www.cloudcompare.org/

  12. Combes SA, Dudley R. Turbulence-driven instabilities limit insect flight performance. Proc Natl Acad Sci USA. 2009;106:9105–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Conchou L, Lucas P, Meslin C, Proffit M, Staudt M, Renou M. Insect odorscapes: from plant volatiles to natural olfactory scenes. Front physiol. 2019;10:972.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Dangles O, Irschick BD, Chittka BL, Casas BJ. Variability in sensory ecology: expanding the bridge between physiology and evolutionary biology. Q Rev Biol. 2009;84(1):51–74.

    Article  PubMed  Google Scholar 

  15. Edelhoff H, Signer J, Balkenhol N. Path segmentation for beginners: an overview of current methods for detecting changes in animal movement patterns. Mov Ecol. 2016;4(1):1–21.

    Article  Google Scholar 

  16. Edomwande C, Barbosa F. The influence of predation risk on mate signaling and mate choice in the lesser waxmoth Achroia grisella. Sci Rep. 2020;10(1):1–8.

    Article  Google Scholar 

  17. Endler JA. Signals, signal conditions, and the direction of evolution. Am Nat. 1992;139:S125–53.

    Article  Google Scholar 

  18. Endler JA, Basolo AL. Sensory ecology, receiver biases and sexual selection. Trends Ecol Evol. 1998;13(10):415–20.

    Article  CAS  PubMed  Google Scholar 

  19. Ercit K, Gwynne DT. Darwinian balancing selection: predation counters sexual selection in a wild insect. Evolution. 2015;69(2):419–30.

    Article  PubMed  Google Scholar 

  20. Farkas SR, Shorey HH, Gaston LK. Sex pheromones of Lepidoptera. Influence of pheromone concentration and visual cues on aerial odor-trail following by males of Pectinophora gossypiella. Annal Entomol Soc Am. 1974;67:633–8.

    Article  Google Scholar 

  21. Farrell JA, Murlis J, Long X, Li WEI, Cardé RT. Filament-based atmospheric dispersion model to achieve short time-scale structure of odor plumes. Environ Fluid Mech. 2002;2(1):143–69.

    Article  Google Scholar 

  22. Fauvergue X, Hopper KR, Antolin MF. Mate finding via a trail sex pheromone by a parasitoid wasp. Proc Natl Acad Sci. 1995;92(3):900–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Ferner MC, Weissburg MJ. Slow-moving predatory gastropods track prey odors in fast and turbulent flow. J Exp Biol. 2005;208(5):809–19.

    Article  PubMed  Google Scholar 

  24. Ferrero DM, Lemon JK, Fluegge D, Pashkovski SL, Korzan WJ, Datta SR, Liberles SD. Detection and avoidance of a carnivore odor by prey. Proc Natl Acad Sci. 2011;108(27):11235–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Golov Y, Liberzon A, Gurka R, Soroker V, Jurenka R, Harari A. Navigation in an odorant-landscape: mate finding and mate choice in a nocturnal moth. Entomologia Generalis. 2022;42:323–34.

    Article  Google Scholar 

  26. Gonzalez-Karlsson A, Golov Y, Steinitz H, Moncaz A, Halon E, Horowitz AR, Harari AR. Males perceive honest information from female released sex pheromone in a moth. Behav Ecol. 2021;32(6):1127–37.

    Article  Google Scholar 

  27. Greenfield MD. Moth sex pheromones: an evolutionary perspective. Fla Entomol. 1981;64(1):4–17.

    Article  Google Scholar 

  28. Harari AR, Steinitz H. The evolution of female sex pheromones. Curr Zool. 2013;59(4):569–78.

    Article  Google Scholar 

  29. Harari AR, Sharon R. Chemical communication. In: Gordon R, Seckbach J, editors. Biocommunication: sign-mediated interactions between cells and organisms. Berlin: World Scientific Publishing; 2017. p. 229–56.

    Chapter  Google Scholar 

  30. Harari AR, Steinitz H. The evolution of female sex pheromones. Current Zoology. 2013;59:569–78.

    Article  Google Scholar 

  31. Harari AR, Zahavi T, Thiéry D. Fitness cost of pheromone production in signaling female moths. Evolut Int J Org Evolut. 2011;65(6):1572–82.

    Article  Google Scholar 

  32. Hebets E. Current status and future directions of research in complex signaling. 2011.

  33. Hildebrand JG, Shepherd GM. Mechanisms of olfactory discrimination: converging evidence for common principles across phyla. Annu Rev Neurosci. 1997;20(1):595–631.

    Article  CAS  PubMed  Google Scholar 

  34. Kuenen LPS, Cardé RT. Effects of moth size on velocity and steering during upwind flight toward a sex pheromone source by Lymantria dispar (Lepidoptera: Lymantriidae). J Insect Behav. 1993;6(2):177–93.

    Article  Google Scholar 

  35. Lacey MJ, Sanders CJ. Chemical composition of sex pheromone of oriental fruit moth and rates of release by individual female moths. J Chem Ecol. 1992;18:1421–35.

    Article  CAS  PubMed  Google Scholar 

  36. Leahy TC, Andow DA. Egg weight, fecundity, and longevity are increased by adult feeding in Ostrinia nubilalis (Lepidoptera: Pyralidae). Ann Entomol Soc Am. 1994;87(3):342–9.

    Article  Google Scholar 

  37. Levi-Zada A, Byers JA. Circadian rhythms of insect pheromone titer, calling, emission, and response: a review. Sci Nat. 2021;108(5):1–20.

    Article  Google Scholar 

  38. Lloyd JE. Mating behavior and natural selection. Florida Entomol. 1979;62(1):17–34.

    Article  Google Scholar 

  39. Lonsdale DJ, Frey MA, Snell TW. The role of chemical signals in copepod reproduction. J Mar Syst. 1998;15(1–4):1–12.

    Article  Google Scholar 

  40. Mafra-Neto A, Cardé RT. Fine-scale structure of pheromone plumes modulates upwind orientation of flying moths. Nature. 1994;369(6476):142–4.

    Article  CAS  Google Scholar 

  41. Mafra-Neto A, Cardé RT. Influence of plume structure and pheromone concentration on upwind flight of Cadra cautella males. Physiol Entomol. 1995;20(2):117–33.

    Article  Google Scholar 

  42. Marsh D, Kennedy JS, Ludlow AR. An analysis of anemotactic zigzagging flight in male moths stimulated by pheromone. Physiol Entomol. 1978;3(3):221–40.

    Article  Google Scholar 

  43. Ortega-Jimenez VM, Badger M, Wang H, Dudley R. Into rude air: hummingbird flight performance in variable aerial environments. Philos Trans Royal Soc B: Biol Sci. 2016;371(1704):20150387.

    Article  Google Scholar 

  44. Ortega-Jimenez VM, Greeter JS, Mittal R, Hedrick TL. Hawkmoth flight stability in turbulent vortex streets. J Exp Biol. 2013;216(24):4567–79.

    PubMed  Google Scholar 

  45. Pham HT, McNamara KB, Elgar MA. Age-dependent chemical signalling and its consequences for mate attraction in the gumleaf skeletonizer moth, Uraba lugens. Anim Behav. 2021;173:207–13.

    Article  Google Scholar 

  46. Ravi S, Crall JD, Fisher A, Combes SA. Rolling with the flow: bumblebees flying in unsteady wakes. J Exp Biol. 2013;216(22):4299–309.

    PubMed  Google Scholar 

  47. Riffell JA, Abrell L, Hildebrand JG. Physical processes and real-time chemical measurement of the insect olfactory environment. J Chem Ecol. 2008;34(7):837–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Robinson EM, Smee DL, Trussell GC. Green crab (Carcinus maenas) foraging efficiency reduced by fast flows. PLoS ONE. 2011;6(6): e21025.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Ronald KL, Fernández-Juricic E, Lucas JR. Taking the sensory approach: how individual differences in sensory perception can influence mate choice. Anim Behav. 2012;84(6):1283–94.

    Article  Google Scholar 

  50. Shine R, Shetty S. The influence of natural selection and sexual selection on the tails of sea-snakes (Laticauda colubrina). Biol J Lin Soc. 2001;74(1):121–9.

    Article  Google Scholar 

  51. Soini HA, Linville SU, Wiesler D, Posto AL, Williams DR, Novotny MV. Investigation of scents on cheeks and foreheads of large felines in connection to the facial marking behavior. J Chem Ecol. 2012;38:145–56.

    Article  CAS  PubMed  Google Scholar 

  52. Svensson GP, Strandh M, Löfstedt C Movements in the olfactory landscape. In animal movement across scales. In: Hansson LA, Åkesson S, editors. Oxford, UK: Oxford University Press; 2014. pp. 45–66.

  53. Svensson M. Sexual selection in moths: the role of chemical communication. Biol Rev. 1996;71(1):113–35.

    Article  Google Scholar 

  54. Talley JL, White EB, Willis MA. A comparison of odor plume-tracking behavior of walking and flying insects in different turbulent environments. J Exper Biol. 2023;226(2):jeb244254.

    Article  Google Scholar 

  55. Tuttle MD, Ryan MJ. Bat predation and the evolution of frog vocalizations in the neotropics. Science. 1981;214(4521):677–8.

    Article  CAS  PubMed  Google Scholar 

  56. Vickers NJ. Mechanisms of animal navigation in odor plumes. Biol Bull. 2000;198(2):203–12.

    Article  CAS  PubMed  Google Scholar 

  57. Ward S, Moller U, Rayner JMV, Jackson DM, Bilo D, Nachtigall W, Speakman JR. Metabolic power, mechanical power and efficiency during wind tunnel flight by the European starling Sturnus vulgaris. J Exp Biol. 2001;204(19):3311–22.

    Article  CAS  PubMed  Google Scholar 

  58. Wäschke N, Meiners T, Rostás M. Foraging strategies of parasitoids in complex chemical environments. Chemical ecology of insect parasitoids 2013;37–63‏.

  59. Wäckers FL, Romeis J, van Rijn P. Nectar and pollen feeding by insect herbivores and implications for multitrophic interactions. Annu Rev Entomol. 2007;52(1):301–23.

    Article  PubMed  Google Scholar 

  60. Webster B, Cardé RT. Use of habitat odour by host-seeking insects. Biol Rev. 2017;92(2):1241–9.

    Article  PubMed  Google Scholar 

  61. Weissburg MJ. The fluid dynamical context of chemosensory behavior. Biol Bull. 2000;198(2):188–202.

    Article  CAS  PubMed  Google Scholar 

  62. Weissburg M, Atkins L, Berkenkamp K, Mankin D. Dine or dash? Turbulence inhibits blue crab navigation in attractive–aversive odor plumes by altering signal structure encoded by the olfactory pathway. J Exp Biol. 2012;215(23):4175–82.

    Article  PubMed  Google Scholar 

  63. Willis MA, Baker TC. Effects of intermittent and continuous pheromone stimulation on the flight behaviour of the oriental fruit moth Grapholita molesta. Physiol Entomol. 1984;9(3):341–58.

    Article  Google Scholar 

  64. Wyatt TD. How animals negotiate odor space in evolutionary-and real-time. Flavour. 2014;3(1):1–1.

    Google Scholar 

  65. Xie J, De Clercq P, Zhang Y, Wu H, Pan C, Pang H. Nutrition-dependent phenotypes affect sexual selection in a ladybird. Sci Rep. 2015;5(1):13111.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Yohe LR, Brand P. Evolutionary ecology of chemosensation and its role in sensory drive. Curr Zool. 2018;64(4):525–33.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Zimmer-Faust RK, Finelli CM, Pentcheff ND, Wethey DS. Odor plumes and animal navigation in turbulent water flow: a field study. Biol Bull. 1995;188(2):111–6.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank Prof. Lubin for her final editing, Eyal Halon for his excellent advice and practical help, and the Chief Scientist of the Ministry of Agriculture, Israel, for funding the research (Research # 13-28-0003).

Funding

The study was supported by grant #13–28-0003 from the Chief Scientist of the Ministry of Agriculture, Israel.

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Authors and Affiliations

  1. Department of Entomology, The Volcani Center, Rishon LeTsiyon, Israel

    Yiftach Golov & Ally Harari

  2. Faculty of Exact Sciences, Porter School of Environment and Earth Sciences, Tel Aviv University, Tel Aviv, Israel

    Yiftach Golov

  3. Department of Physics and Engineering Science, Coastal Carolina University, Conway, SC, USA

    Roi Gurka

  4. School of Mechanical Engineering, Tel Aviv University, Tel Aviv, Israel

    Alexander Liberzon

  5. Department of Biology and Environment, University of Haifa-Oranim, Haifa, Israel

    Ally Harari

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Contributions

Y. G. wrote the main manuscript text accompanied by the assistance of A. H and R. Gurka. Writing – first draft: Y. G. Writing – review & editing: R. G., A. H. and A. L. Data curation was done at the Labs of A. L. and A.H.; Y. G. did the data collection and data analysis. Funding acquisition: A. Harari, A. Liberzon, Methodology: Y. Golov, A. Harari, A. Liberzon, R. Gurka. Supervision: R. Gurka, A. H and A. L. Y.G. did the primary drafts of data visualization with post-editing by A.H and R.G. All authors reviewed the manuscript.

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Golov, Y., Gurka, R., Liberzon, A. et al. Physical and biological effects on moths’ navigation performance. Mov Ecol 13, 17 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40462-025-00547-4

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Keywords

Movement Ecology

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