Evaluating mate encounter and walking dispersal dynamics of termites using posture tracking and behavioral simulation

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Yet, each colony begins with a single mating encounter between a female and a male. After seasonal dispersal flights, termite dealates walk to search for a mating partner and a nest site. This initial stage is critical for dispersal, infestation, and invasion success. However, the search dynamics and success of these walking termites remain poorly understood, especially under varying environmental conditions. In this study, I investigated mate-searching and post-pairing dispersal behaviors in Coptotermes formosanus , one of the most damaging subterranean termites, by reanalyzing observations in the experimental arena using a deep-learning posture tracking approach. I show that termites can walk an average of 23 m within 15 minutes, with estimated displacements up to 18.74 m. Nest-searching tandem pairs showed more directional and stable motion with higher dispersal potential than mate-searching single termites because of the movement coordination. Simulations parameterized by termite observations showed that urban light attraction greatly contributed to the pairing success of termites, even with a low termite population density. These findings suggest that simple movement rules and environmental cues can enhance mating encounters and dispersal, facilitating infestation and invasion. Comparative behavioral studies across termite species may link the movement ecology of termites with their pest status and invasive potential. Alate behavior colony foundation nest establishment movement ecology urban entomology light pollution courtship Formosan subterranean termite Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Among more than 3,000 species, some termites are serious structural pests, causing damage of $ 40 billion annually across the world, as estimated in 2010 (Rust and Su, 2012 ). In particular, invasive termite species have a substantial impact; for example, Coptotermes formosanus is listed as one of the top 10 most costly invasive species (Cuthbert et al., 2022 ). Termite studies have traditionally focused on mature colonies, since damage occurs only after colonies reach maturity (Gordon et al., 2022 ; Su and Scheffrahn, 1998 ) (Fig. 1 ). However, even though the mature colony is made up of millions of individuals, all termite colonies begin with a monogamous mating pair of a female and a male (Nutting, 1969 ) (Fig. 1 ) with a few exceptions (Perdereau et al., 2015 ). This highly mobile mate-pairing stage is a determinant of the initial infestation, population dynamics, and invasion success. Yet, this critical stage has been understudied compared to the mature colonies. In this study, I explore the mate-finding and dispersal dynamics of a termite, Coptotermes formosanus Shiraki (Blattodea: Heterotermitidae), especially focusing on their walking behaviors. During a particular season, a large number of alates (winged reproductive individuals) fly off from their parental colony nests (Fig. 1 ). There are three immediate tasks for alates: 1) dispersal from their original place, 2) finding a mating partner, and 3) finding a nest site to start a colony. This information on C. formosanus is summarized in a chapter of a book on this species, where dispersal flight is relatively well described (Chouvenc, 2023 ). The dispersal flight of C. formosanus initiates at dusk (late twilight) and continues for 15 minutes to an hour (Chouvenc, 2023 ). Alates of C. formosanus show a variable ability to disperse during flight. Direct observation recorded dispersal distance up to 460 m (Ikehara, 1966 ), and extensive mark recapture efforts showed that they can disperse 621 m on average and up to 1,300 m (Messenger and Mullins, 2005 ; Mullins et al., 2015 ), while genetic analyses of alates and surrounding colonies suggest alates dispersed 20–510 m away (Simms and Husseneder, 2009 ). Collectively, these indicate that alates of C. formosanus have a decent ability to disperse and expand their distribution ranges and thus are useful for distribution surveys. However, as a socially monogamous insect, females and males of C. formosanus must find a partner after dispersion and wing shedding. Unlike social Hymenoptera, all important mating processes happen during walking, i.e., finding a mating partner, engaging in pairing courtship, and finding a nest site. Thus, quantifying their post-dispersal movement is essential to understanding mating success. After landing on the ground and shedding their wings, both females and males engage in mate search by walking. This mate search is assumed to be a random search (Mizumoto and Dobata, 2019 ), indicating that termites do not know where their partner is until they encounter it, because C. formosanus termites do not rely on vision (Mizumoto and Bourguignon, 2022 ) or long-distance attracting chemicals (Chouvenc et al., 2020 ; Raina et al., 2003 ) to locate a partner. Before encountering a partner, both females and males actively search for a partner to maximize the search area (Mizumoto and Dobata, 2019 ). Once encountered, a female and male pair perform tandem running behavior, with the leader female and the follower male coordinating motion, while searching for a suitable nest site. In tandem running, a female leader determines the course of the movement (Mizumoto et al., 2021 ; Valentini et al., 2020 ), whereas the follower males maintain contact with their antennae and pulps (Mizumoto and Reiter, 2025 ; Raina et al., 2003 ). In case of accidental separation between partners, a female leader pauses to wait for the partner, and a male follower engages in an area-restricted search, which is an effective reunion strategy for the strayed partners (Mizumoto et al., 2020 ; Mizumoto and Dobata, 2019 ). Encounters of the same sex may also result in tandem runs (Mizumoto et al., 2024a ), but they are rarer than those of other species (Mizumoto et al., 2022 ). Therefore, on the ground, termites dynamically alternate mate and nest searches until they settle in an available and suitable space for colony foundation (Chouvenc, 2023 ; Su et al., 1989 ). These observations provide important behavioral information for termite dealates. However, the dispersion-encounter dynamics of dealates remain unknown, e.g., how far termites can travel after shedding their wings or the effective density required for mate searchers to encounter their partner. In this study, I address these questions by reanalyzing termite searching strategies studied in a previous study and building a behavioral simulation. Especially, Mizumoto and Dobata 2019 studied the movement patterns of termite dealates in both Coptotermes formosanus and Reticulitermes speratus to investigate their mate searching strategies. This study obtained the movement trajectories of termite dealates in a petri dish arena, by tracking their body centers with a background subtraction technique, i.e., UMATracker (Yamanaka and Takeuchi, 2018 ). Since then, more video tracking tools have become available, and there have been many advancements in deep learning-based posture tracking. In this study, by updating the analysis, I reanalyze the same video with one of these advanced tools, i.e., SLEAP (Pereira et al., 2022) to track termite movements by body parts. Then, using posture information, I attempted to unwrap termite movements in a dish to the approximate open space to grasp their dispersal abilities by walking. Furthermore, using the movement parameters of termites, I developed a mate searching simulation and tested the effect of density and urban lights on mating encounter dynamics. Methods Behavioral data To investigate the walking behavior of termite dealates, I used the videos obtained in a previous study (Mizumoto and Dobata, 2019). In this study, experiments with C. formosanus were performed to study the adaptive mate search strategy used by termites. Alates were collected using light trapping or from two colonies of C. formosanus nesting wood in Wakayama, Japan in June 2017. After dispersal flights in the lab, termites that shed their wings were used for observations. Observations were performed in a petri dish (Ø = 145 mm) filled with a moistened plaster. They observed termites under two different conditions: in single searching experiments, they introduced a female or a male to the experimental arena and recorded their movement for 30 min, while in tandem running observations, they introduced one female and one male together to the arena and recorded for 60 min. A total of 22 single females, 21 single males, and 20 tandem-running pairs were observed. All videos were analyzed using SLEAP v 1.4.0 (Pereira et al., 2022) to estimate the movement of the body parts of each individual. The model was based on the model developed for C. formosanus in a previous study (Mizumoto and Reiter, 2025), with a 17-node skeleton capturing key anatomical landmarks: antenna tips (left and right), antenna middles, antenna bases, head (centered at the mouthparts), segmental boundaries (head–pronotum, pronotum–mesonotum, metanotum–abdomen), abdomen tip, and all six legs (fore, mid, and hind; left and right). I only used data from the head and abdominal tip for movement analysis. Owing to the video quality, the detection accuracy of the legs or antennae was very low, but including these improved the tracking accuracy of the head and abdomen tips. I trained a U-Net-based model with a multi-animal top-down approach, with a receptive field size of 76 pixels for the centroid and 316 pixels for the centered instance, on Nvidia GeForce RTX 4090, where augmentation was performed by rotating images from -180 to 180 °. Video analysis was performed for tandem running and single termites separately because of the setup difference between these two experiments, where I finished tandem running first and then used the model developed for tandem running to develop the model for single termites. I labeled 65 frames from 15 videos in tandem running, while 61 frames from 25 videos in single termites. While tracking after inference, the instance similarity method with the greedy matching method was used. All pose estimation data were converted into HDF5 files for further analysis. Python was used to format all HDF5 files for further analysis and convert them into FEATHER files for analysis in R (R Core Team, 2024). We employed a linear interpolation method to address the missing values in the dataset. After scaling all data from pixels to millimeters, we used a median filter with a kernel size of five to reduce noise. All analyses were performed after downsampling at 5 FPS. From the trajectories, the following kinetic variables were obtained: First, I determined the body center as the middle position between the head and the abdomen tip. The displacements of the body center positions were computed for every frame to obtain the instantaneous movement speed. The changes in the movement speed (acceleration/deceleration) and movement direction were also computed using the displacements. Independent of the movement direction, the termite heading direction was computed as the vector from the abdominal tip to the head. For tandem running observations, I defined tandem running as a state in which the distance between the female abdominal tip and the male head is shorter than 3.1 mm (Mizumoto and Reiter, 2025), where short separation or short running (< 1 s) was smoothed. Then, I analyzed movement patterns only during tandem running behavior to compare with single dealates. Unwrapping movements in a dish to open space In the dish arena, termite movements are bounded by the arena wall, making it impossible to investigate their dispersal behavior (Nagaya et al., 2017). In this study, however, to grasp dispersal ability by walking in termite dealates, I converted the movement trajectories recorded in a circular dish into approximated open-space movements by applying a series of corrections to movements bounded by a constrained space. The conversions addressed two main artifacts: wall-following behavior and mismatches between heading and movement directions caused by the dish walls. Note that these conversions do not completely reflect their motion in open space; instead, I aimed to approximate how far termites could disperse if there were no boundaries in a dish (Figure S1-3). First, termites in a dish often exhibit a wall-following behavior, moving along the perimeter of the dish in a smooth and curved trajectory (Miramontes et al., 2014; Paiva et al., 2020; Shimoji et al., 2019). I assume that termite movements were biased due to the wall and that termites would maintain their heading direction rather than curving along a dish wall in an open space. Thus, I considered that termites were forced to turn at angles that required them to rotate along the wall. To correct this, the x-y coordinates were converted into polar coordinates relative to the center of the arena. I searched for sequences of frames where termites moved more than 10 mm in the same direction as the angular coordinates. For each of these events, I obtained the number of angles the termite rotated and then adjusted the trajectory by rotating the positions to extend the path outward, unwrapping the wall-following sequences (Figure 2A). Second, near the wall, termite movements are often bounded by the wall, creating many discrepancies between the heading direction (direction from the abdominal tip to the head) and the actual movement direction. These discrepancies were fixed near the wall (defined as the outer half region in the area) by rotating the trajectory around the previous location to align it with the heading direction. This assumes that the termite attempts to move forward along its body axis without redirection arising from the dish or tracking artifacts (Figure 2B). Statistical analysis I used linear mixed models (LMMs) to analyze the speed, speed change, and turning patterns, using the functions lmer() in the package ‘lme4’ (Bates and Maechler, 2015) and lme() in ‘nlme’ (Pinheiro, 2011). The likelihood ratio (type II) test was used to examine the statistical significance of each explanatory variable. I investigated the relationship between speed and speed change using an LMM with speed change as the response variable, and speed, unit type (single or tandem leader), and their interaction as fixed effects. Video ID nested within the original colony was included as a random effect (random intercept). A similar LMM tested differences in speed between units, with unit type as the fixed effect. In addition, to compare variability in these parameters between units, I compared two LMMs, one assuming equal variance and another allowing variance to differ between units, using likelihood ratio tests. Also, travel distance was compared using an LMM with travel distance as the response, unit type as a fixed effect, and colony as a random effect. Distance was calculated by summing mean step lengths (every 0.2 s) over 15 minutes for the aid of interpretation. Next, I investigated the dispersal patterns of trajectories unwrapped to simulate open space. For the tandem running observations, I focused on each tandem running event rather than each video, as the latter included both tandem running and separations. First, for each trajectory, the displacements from the beginning points at 15-minute time points were extracted and compared between units using a similar LMM as above. The mean squared displacement (MSD) was computed to investigate the diffusive properties of the unwrapped trajectories. MSD is defined as the average squared distance from the starting point after a delay time τ, and follows MSD ~ τ α , where α indicates the diffusion type: α = 1 for Brownian (normal), α 1 for superdiffusive motion (Viswanathan et al., 2011). MSDs were obtained in the entire range of each trajectory, using the function computeMSD() in the package ‘flowcatchR’ (Marini, 2017). To obtain the diffusion properties, I examined the relationship between MSD and τ using a log-log transformation. The fitting was restricted to a subset of datasets (0.2, 0.4, 0.6, 0.8, 1, 2, 4, 6, …, 1000) to avoid oversampling at a larger τ. The fitting was performed using an LMM with each trajectory identity included as a random slope. The slope α obtained from this regression corresponds to the scaling exponent, which characterizes the diffusion regime (e.g., sub-diffusive, diffusive, or super-diffusive). Results Both single dealates and tandem leaders showed a clear correlation between movement speed and change in speed: termites tended to speed up after slower movements and slow down after faster ones (Figure 3AB). However, the slopes of this response differed between the two groups (LMM, interaction: χ 2 1 = 28.18, P < 0.001), with singles showing more sensitive speed adjustments (slope, single: -0.184, leader: -0.176). Their average speeds did not differ (LMM, χ 2 1 = 1.2, P = 0.273), but both speed and acceleration were more variable in singles than leaders, as seen in the broader data distributions (Figure 3AB). Models allowing group-specific variances fit the data much better than those assuming equal variance (speed: χ 2 1 = 17010.06, P < 0.001; change in speed: χ 2 1 = 21499.91, P < 0.001), confirming reduced variability in tandem leaders. The turning patterns showed a similar pattern: singles exhibited broader distribution than tandem leaders (Figure 3CD), supported by model comparison (χ 2 1 = 27673.09, P < 0.001). Interestingly, the relationship between speed and turning was different between groups. In singles, the turning angles became more variable according to movement speed (Figure 3C). On the other hand, tandem leaders decreased turning angle variabilities when moving steadily, with a local minimum in turning SD around 3.8 mm/0.2 sec (Figure 3D). Termites continued moving throughout the 15-minute observation, despite the bounded arena. Travel distance did not differ significantly between singles and leaders (χ²₂ = 1.52, P = 0.469; Figure 4A). Notably, termites walked 23 ± 4.2 m (mean ± S.D.) in 15 min on average. After applying trajectory unwrapping to project paths into open space (Figure 4CD, Figures S1–S3), tandem leaders dispersed further than singles (χ²₁ = 5.03, P = 0.025; Figure 4B): singles dispersed 6.5 ± 3.7 m from the origin, whereas leaders dispersed 9.6 ± 4.8 m. The MSD analysis showed that tandem leaders exhibited more diffusive movement than single termites (Figure 4CD). The estimated diffusive exponent α was 1.65 (with S.D. of 0.12 by the random slope, LMM) for singles, while 1.80 (with S.D. of 0.12 by the random slope, LMM) in tandem leaders. In either case, the trajectories showed superdiffusive properties, as observed in arthropods in (pseudo-) open spaces (Johnson et al., 1992; Mizumoto et al., 2024b; Nagaya et al., 2017; Seuront and Stanley, 2014). Simulations I used an individual-based model to examine the dynamics of termite mating encounters based on empirically estimated movements in open space. Simulations took place within a square area of size L ₐᵣₑₐ × L ₐᵣₑₐ under periodic boundary conditions. Two mate-search scenarios were considered (Figure 5A): (i) without light , where all individuals were initially distributed randomly across the entire area, and (ii) with light , where individuals were first attracted to a light source before shedding their wings and began their search from a concentrated square region of size L light × L light . In both scenarios, females and males moved until they encountered an opposite-sex individual. An encounter was defined as the distance between their centers becoming smaller than φ = 10 mm, following Mizumoto and Dobata (2019). Individuals moved via correlated random walks, with both speed and turning angle correlated across timesteps. Speed at the current timestep was a function of the previous speed, reflecting empirical evidence that acceleration correlates with speed (Figure 3). Speed was updated using the following relationship: , where parameter values were obtained by fitting the empirical datasets of solo individuals, a = -0.184, b = 0.910, σ = 0.628. Turning angles also followed a Laplace distribution with scale parameter σ = 0.164. I used the Laplace distribution instead of common angular distributions, such as wrapped Cauchy or von Mises distributions, because the empirically observed turning angles were sharply peaked around zero (Figure 3), and the Laplace distribution provided a better fit. Each simulation timestep represented 0.2 seconds, matching the empirical data sampling rate of 5 FPS. Simulations ran for 30 minutes (9,000 steps), and the number of mating encounters was recorded at every step. Initial population sizes were set to 100, 1,000, and 10,000 individuals with a 1:1 sex ratio, corresponding to small, medium, and large swarming events (Chouvenc et al., 2017; Higa and Tamashiro, 1983; Sugio, 2019). The search area was fixed at L ₐᵣₑₐ = 30 m, and when light attraction was present, the concentration area was L light = 3 m. Simulations were implemented in C++ and executed in R using the Rcpp package (Eddelbuettel and Balamuta, 2018). The results of the sensitivity analysis of these parameters are in the supplementary materials (Figure S4). The simulation results clearly showed the Allee effects on the termite mating encounters as observed in a termite (Kusaka and Matsuura, 2017). At higher densities, more individuals successfully found a mate, and the presence of light greatly increased encounter probability by locally concentrating termites (Figure 5B, S4). With only 100 randomly distributed individuals in a 30 × 30 m area, successful encounters were rare, indicating the inefficiency of pure random search. However, when local density increased, encounter rates rose substantially. Notably, even with a limited population (e.g., 100 individuals), light attraction increased encounter rates beyond those seen in larger populations without light (Figure 5). Discussion In termite dealates, walking to search for a mating partner and a suitable nest site is an essential first task after dispersal. The comparison shows that the movement of tandem running pairs (nest site searching) is more diffusive and more stable than the movement of single termites (mate searching). The moving speed of tandem leaders is less variable than that of single termites, and the turning angles are also less variable (Fig. 3 ). Such a stable and more straight motion by tandem leaders resulted in dispersing more distances from the initial points, even though the total travel distance was not different from single termites (Fig. 4 ). This behavioral difference between single termites and tandem leaders makes sense from both ultimate and proximate points of view. From an ultimate perspective, more directed motion during tandem running allows pairs to move away from their initial encounter site. Mate searching behavior is mutual search, where both females and males search for each other, and even slow-moving or pausing behavior can achieve a higher encounter rate for one sex (Foffi et al., 2025 ; Mizumoto et al., 2017 ; Mizumoto and Dobata, 2018 ; Reynolds, 2006 ). On the other hand, in nest-site search, the advantage of moving a greater distance will be higher than in mate search, as the nest-site does not move to find a site searcher. Furthermore, if termite mate searchers are clumped in one location, dispersing from there may be advantageous, as encountering another mate searcher can lead to the interruption of tandem running (Mizumoto et al., 2020 ). From a proximate perspective, more stable and straight motion of tandem running may be the consequence of movement coordination. The stable and directed movement seen in tandem running may result from the coordination between the leader and the follower. In this behavior, leaders slow down and followers speed up when the distance increases, and vice versa when they are closer (Mizumoto and Bourguignon, 2022 ; Mizumoto and Reiter, 2025 ; Valentini et al., 2020 ). Similar speed controls can be observed in ant tandem running (Franks and Richardson, 2006 ; Mizumoto et al., 2023 ; Valentini et al., 2020 ) or different types of movement coordination (e.g., fish (Schaerf et al., 2021 )). Also, to maintain contact between leaders and followers, the possible movement directions of leaders may have been limited compared to when they are alone, because sharp turns by leaders often result in the interruption of tandem running (Mizumoto et al., 2020 ; Valentini et al., 2020 ). In this sense, even though tandem running is a simple movement coordination, cooperation between partners can, in turn, affect the pair-level movement patterns. Artificial light, especially in urban areas, is generally harmful to nocturnal flying insects (Owens et al., 2020 ), e.g., by trapping insects near the light source for a long period and eliminating the time window for other essential activities (Kasai and Hironaka, 2024 ). However, C. formosanus (and several other termites) might benefit from artificial lights. Termites exhibit a rapid behavioral switch: while alates are attracted to lights, dealates show negative phototaxis soon after shedding their wings (Chouvenc, 2023 ; Ferreira and Scheffrahn, 2011 ; Ohmura et al., 2014 ). This reduces the chance of being trapped near lights and suggests that tandem behavior remains unaffected by urban lighting (Mizumoto and Bourguignon, 2022 ). Previous studies suggest that urban lights should have contributed to their successful invasion processes (Chouvenc, 2025 ), which is indirectly supported by the fact that the diurnal flight species, C. testaceus , is not as invasive as C. formosanus or C. gestroi (Scheffrahn et al., 2015 ). The simulation results also support this hypothesis. Using empirically observed walking parameters, I show that low densities (e.g., 100 termites in a 30×30 m² area) are insufficient for successful mate encounters by random search, but artificial lights can inflate the encounter rate, comparable to having ten times more individuals in the same area (Fig. 5 , S4). This effect may make small swarming events more productive (Chouvenc et al., 2017 ; Higa and Tamashiro, 1983 ; Sugio, 2019 ) and facilitate colony establishment in invasion frontiers, where population sizes are usually limiting. Note that the unwrapping method is not a perfect approximation of open space movements. It introduces some artifacts, especially when termites make abrupt 180° turns while following the wall. This can be interpreted as that termites attempted to turn in some direction but were constrained by the wall, resulting in a 180° turn. These sharp turns appear in the unwrapped data as large directional changes (Figures S1 -3). While the walls likely influence behavior (Scharf et al., 2024 ). I consider these effects minimal for searching behaviors in termite dealates. Unlike other solitary insects, termites have only a short time window to find a mate and nest site; failure to do so results in death (Chouvenc, 2023 ; Mizumoto et al., 2024b , 2016 ). At this stage, searching is the only task for termites, and they remain highly active (Fig. 4 B), consistent with the field observations. Still, further studies will be required to better estimate the termite on-foot dispersal ability, including mark recapture on termite dealates (Mullins et al., 2015 ), or collecting termites using a nest site trap in the field environments (Nkunika, 1988 ; Su et al., 1989 ). While caution is necessary when applying this method to non-termite taxa, it may provide useful insights for other pest insects that rely on walking movement, especially in urban settings (Socha and Zemek, 2003 ; Suchy and Lewis, 2011 ). Mate pairing is a rarely emphasized phase in termite life cycles, yet it is a crucial starting point for colony foundation and varies widely among species (Mizumoto et al., 2022 ; Nutting, 1969 ). High density is clearly important for Coptotermes species that use random encounters as a primary method of the pairing process, but this is not always the case in other invasive pest species (Evans et al., 2013 ), especially in Kalotermitidae. For example, Cryptotermes brevis and Incisitermes minor are two major drywood pest species in the US and are expanding their distributions in urban settings (Lee et al., 2024 ). Both of these exhibit tandem running courtship behavior, but the density is much smaller than that of Coptotermes termites, and I. minor disperses during the day (Harvey, 1934 ; Minnick, 1973 ). Furthermore, e.g., Cryptotermes domesticus lacks tandem running behaviors (Huang et al., 2007 ), which should have a distinct pairing process for colony foundation. These drywood termites are one-piece nesting termites that do not move to other nesting materials according to colony development (Abe, 1987 ). Thus, selecting a suitable nest site at the time of pairing becomes critical for future colony success. Yet, our knowledge about mate-pairing and nest-site selection in termites remains limited, both in pests and non-pests. Comparative studies across species would be valuable for predicting how termites spread in urban environments. Declarations Funding This study is supported by the USDA National Institute of Food and Agriculture, Hatch project number 7007938. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Data Availability The datasets and codes generated during the current study are available at GitHub, https://github.com/nobuaki-mzmt/DealateDiffusion . The accepted version will be deposited in Zenodo to obtain DOI. Ethics approval This study did not require ethical approval as it involved only the analysis of previously published data. No new data were collected from human or animal subjects. Author Contribution NM is the only author of the manuscript. Acknowledgement I thank Dr. Jian Chen for nominating me for the Collection "Emerging Leaders in Pest Science: Celebrating 100 Years of Innovation,” and all collaborators relating to the series of projects on termite tandem running behavior. I acknowledge the use of ChatGPT, a language model developed by OpenAI, for minor suggestions with respect to the texts and coding. This study is supported by the USDA National Institute of Food and Agriculture, Hatch project number 7007938. References Abe T. 1987. Evolution of life types in termites In: Kawano S, Connell J, Hidaka T, editors. Evolution and Coadaptation in Biotic Communities. Tokyo: University of Tokyo Press. pp. 125–148. Bates DM, Maechler M. 2015. 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Coordination of movement via complementary interactions of leaders and followers in termite mating pairs. Proceedings of the Royal Society B: Biological Sciences 288 :20210998. doi:10.1098/rspb.2021.0998 Mizumoto N, Nagaya N, Fujisawa R. 2024b. Wasted efforts impair random search efficiency and reduce choosiness in mate-pairing termites. The American Naturalist 000–000. doi:10.1086/732877 Mizumoto N, Reiter S. 2025. Maintaining tandem movement cohesion through antennal movements in termites. doi:10.1101/2025.02.13.638054 Mizumoto N, Rizo A, Pratt SC, Chouvenc T. 2020. Termite males enhance mating encounters by changing speed according to density. Journal of Animal Ecology 89 :2542–2552. doi:10.1111/1365-2656.13320 Mizumoto N, Tanaka Y, Valentini G, Richardson TO, Annagiri S, Pratt SC, Shimoji H. 2023. Functional and mechanistic diversity in ant tandem communication. iScience 26 :106418. doi:10.1016/j.isci.2023.106418 Mizumoto N, Yashiro T, Matsuura K. 2016. Male same-sex pairing as an adaptive strategy for future reproduction in termites. Animal Behaviour 119 :179–187. doi:10.1016/j.anbehav.2016.07.007 Mullins AJ, Messenger MT, Hochmair HH, Tonini F, Su N-Y, Riegel C. 2015. Dispersal flights of the Formosan subterranean termite (Isoptera: Rhinotermitidae). Journal of Economic Entomology 108 :707–719. doi:10.1093/jee/tov022 Nagaya N, Mizumoto N, Abe MS, Dobata S, Sato R, Fujisawa R. 2017. Anomalous diffusion on the servosphere : A potential tool for detecting inherent organismal movement patterns. PLoS ONE 12 :e0177480. doi:10.1371/journal.pone.0177480 Nkunika POY. 1988. The biology and ecology of the dampwood termite, Porotermes adamsoni (Froggatt) (Isoptera : Termopsidae) in South Australia. Adelaide: The University of Adelaide. Nutting WL. 1969. Flight and colony foundation. In: Krishna K, Weesner FM, editors. Biology of Termites. New York: Academic Press. pp. 233–282. doi:10.1016/B978-0-12-395529-6.50012-X Ohmura W, Kataoka Y, Kiguchi M. 2014. Difference in phototactic behavior in alates of Coptotermes formosanus Shiraki and Incisitermes minor (Hagen) under laboratory conditions. Japanese Journal of Environmental Entomology and Zoology 25 :39–44. doi:10.11257/jjeez.25.39 Owens ACS, Cochard P, Durrant J, Farnworth B, Perkin EK, Seymoure B. 2020. Light pollution is a driver of insect declines. Biological Conservation 241 :108259. doi:10.1016/j.biocon.2019.108259 Paiva LRD, Marins A, Cristaldo PF, Ribeiro D, Alves SG, Reynolds A. 2020. Scale-free movement patterns in termites emerge from social interactions and preferential attachments 1–39. doi:10.1073/pnas.2004369118/-/DCSupplemental.y Perdereau E, Bagnères A-G, Vargo E l., Baudouin G, Xu Y, Labadie P, Dupont S, Dedeine F. 2015. Relationship between invasion success and colony breeding structure in a subterranean termite. Molecular Ecology 24 :2125–2142. doi:10.1111/mec.13094 Pereira TD, Tabris N, Matsliah A, Turner DM, Li J, Ravindranath S, Papadoyannis ES, Normand E, Deutsch DS, Wang ZY, McKenzie-Smith GC, Mitelut CC, Castro MD, D’Uva J, Kislin M, Sanes DH, Kocher SD, Wang SSH, Falkner AL, Shaevitz JW, Murthy M. 2022. SLEAP: A deep learning system for multi-animal pose tracking. Nature Methods 19 :486–495. doi:10.1038/s41592-022-01426-1 Pinheiro J. 2011. nlme: Linear and nonlinear mixed effects models. R Package Version . R Core Team. 2024. R: A language and environment for statistical computing. Raina AK, Bland JM, Dickens JC, Park YI, Hollister B. 2003. Premating behavior of dealates of the Formosan subterranean termite and evidence for the presence of a contact sex pheromone. Journal of Insect Behavior 16 :233–245. doi:10.1023/A:1023967818906 Reynolds AM. 2006. Optimal scale-free searching strategies for the location of moving targets: New insights on visually cued mate location behaviour in insects. Physics Letters A 360 :224–227. doi:10.1016/j.physleta.2006.08.047 Rust MK, Su NY. 2012. Managing social insects of urban importance. Annual Review of Entomology 57 :355–375. doi:10.1146/annurev-ento-120710-100634 Schaerf TM, Herbert-Read JE, Ward AJW. 2021. A statistical method for identifying different rules of interaction between individuals in moving animal groups. Journal of the Royal Society, Interface 18 :20200925. doi:10.1098/rsif.2020.0925 Scharf I, Hanna K, Gottlieb D. 2024. Experimental arena settings might lead to misinterpretation of movement properties. Insect Science 31 :271–284. doi:10.1111/1744-7917.13213 Scheffrahn RH, Carrijo TF, Krecek J, Su N-Y, Szalanski AL, Austin JW, Chase JA, Mangold JR. 2015. A single endemic and three exotic species of the termite genus Coptotermes (Isoptera, Rhinotermitidae) in the New World. Arthropod Systematics and Phylogeny 73 :333–348. Seuront L, Stanley HE. 2014. Anomalous diffusion and multifractality enhance mating encounters in the ocean. Proceedings of the National Academy of Sciences of the United States of America 111 :2206–11. doi:10.1073/pnas.1322363111 Shimoji H, Mizumoto N, Oguchi K, Dobata S. 2019. Caste-biased locomotor activities in isolated termites. Physiological Entomology 45 :50–59. doi:10.1111/phen.12315 Simms D, Husseneder C. 2009. Assigning individual alates of the Formosan Subterranean termite (Isoptera: Rhinotermitidae) to their colonies of origin within the context of an area-wide management program. Sociobiology 53 :631–650. Socha R, Zemek R. 2003. Wing morph-related differences in the walking pattern and dispersal in a flightless bug, Pyrrhocoris apterus (Heteroptera). Oikos 100 :35–42. doi:10.1034/j.1600-0706.2003.12100.x Su NY, Scheffrahn RH. 1998. A review of subterranean termite control practices and prospects for integrated pest management programmes. Integrated Pest Management Reviews 3 :1–13. doi:10.1023/A:1009684821954 Su N-Y, Scheffrahn RH, Ban PM. 1989. Method to monitor initiation of aerial infestations by alates of the Formosan subterranean termite (Isoptera: Rhinotermitidae) in high-rise buildings. Journal of Economic Entomology 82 :1643–1645. doi:10.1093/jee/82.6.1643 Suchy JT, Lewis VR. 2011. Host-seeking behavior in the bed bug, Cimex lectularius . Insects 2 :22–35. doi:10.3390/insects2010022 Sugio K. 2019. Characteristics of dispersal flight of the Formosan subterranean termite, Coptotermes formosanus Shiraki (Isoptera: Rhinotermitidae) in Okinawa. Japanese Journal of Environmental Entomology and Zoology 30 :63–69. doi:10.11257/jjeez.30.63 Valentini G, Mizumoto N, Pratt SC, Pavlic TP, Walker SI. 2020. Revealing the structure of information flows discriminates similar animal social behaviors. eLife 9 :e55395. doi:10.7554/eLife.55395 Viswanathan GM, Luz M da, Raposo EP, Stanley HE. 2011. The Physics of Foraging: An Introduction to Random Searches and Biological Encounters. Cambridge: Cambridge University Press. Yamanaka O, Takeuchi R. 2018. UMATracker: An intuitive image-based tracking platform. Journal of Experimental Biology 221 :1–24. doi:10.1242/jeb.182469 Additional Declarations No competing interests reported. Supplementary Files SIJPS.pdf Cite Share Download PDF Status: Published Journal Publication published 10 Mar, 2026 Read the published version in Journal of Pest Science → Version 1 posted Editorial decision: Revision requested 11 Dec, 2025 Reviews received at journal 05 Dec, 2025 Reviewers agreed at journal 24 Nov, 2025 Reviews received at journal 12 Aug, 2025 Reviews received at journal 28 Jun, 2025 Reviewers agreed at journal 18 Jun, 2025 Reviewers agreed at journal 16 Jun, 2025 Reviewers invited by journal 10 Jun, 2025 Editor assigned by journal 07 Jun, 2025 Submission checks completed at journal 07 Jun, 2025 First submitted to journal 06 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6837416","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":469177118,"identity":"3bafaea8-fc3b-46dd-a232-0b4b407ef255","order_by":0,"name":"Nobuaki Mizumoto","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYJCCAwkV/+QYGHhgXMI6GB98OHPAmCQtzIYz2w4kNhCtxZz/dJo0b9ud9P4ZucekK3cwyPHdSMCvxbLh7DZpnnPPcmfcyEuTPHuGwViSkBaDg71ALWXMuQ03cswkG9sYEjcQ1HKYF6iFjTldHqqlnrCWY7ybDWe0HU4wgGoBMghpOcO7ERjIaYYbz7xLtmxskzCceeYBAS3nz24ARqWNvNzx3IM3G9ts5PmOE7AFHUiQpnwUjIJRMApGAXYAAHPZTGsYkp7nAAAAAElFTkSuQmCC","orcid":"","institution":"Auburn University","correspondingAuthor":true,"prefix":"","firstName":"Nobuaki","middleName":"","lastName":"Mizumoto","suffix":""}],"badges":[],"createdAt":"2025-06-06 13:23:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6837416/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6837416/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10340-026-02023-3","type":"published","date":"2026-03-10T16:00:29+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":84457451,"identity":"b82a7d92-0e3c-4f12-81cc-70a7e311942d","added_by":"auto","created_at":"2025-06-12 08:15:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1423733,"visible":true,"origin":"","legend":"\u003cp\u003eLife cycle of subterranean termites, as an example of \u003cem\u003eCoptotermes formosanus\u003c/em\u003e. In a season of the year, many alates (winged individuals) fly to disperse. After dispersal, females and males search for mating partners. The encountered pair performed a tandem run to seek a nest site for the colony foundation. The established colony grows into the mature colony, which produces alates again. Among these, only mature colonies with a large number of colony members can damage human properties. Photos are taken from different populations, including Onna-son, Okinawa, Japan, Ishigaki, Okinawa, Japan, and Fort Lauderdale, FL, Florida.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6837416/v1/16584d78a2e2c448157be1ee.png"},{"id":84458014,"identity":"26501ae4-76f2-4f50-8724-28f06b53e05b","added_by":"auto","created_at":"2025-06-12 08:23:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":24265,"visible":true,"origin":"","legend":"\u003cp\u003eUnwrapping trajectories in a dish to open space. (A) Correction of wall-bound rotating motion. The path circulating around the dish was unwrapped by rotating the positions to extend the path outward. (B) Fixing the discrepancy between heading directions and movement directions. Using posture tracking datasets, the movement directions were replaced with heading directions to mimic movements in an open space.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6837416/v1/17f31ddd8f23006a9914d525.png"},{"id":84457456,"identity":"af01ac54-cbc8-4be2-8aea-fc53ed88dfa3","added_by":"auto","created_at":"2025-06-12 08:15:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":98987,"visible":true,"origin":"","legend":"\u003cp\u003eMovement parameters for termite dealates. The lines and colored areas indicate the mean ± S.D., which was calculated by binning the speed by 0.1. The dashed regression lines by the LMM were drawn for the change in speed (acceleration/deceleration). The histograms of each kinetic parameter were also shown.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6837416/v1/a00edc95ef3b859aa99bd38a.png"},{"id":84457461,"identity":"9ebbf97a-7084-42f7-87c9-dd20c9e830b9","added_by":"auto","created_at":"2025-06-12 08:15:17","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":146921,"visible":true,"origin":"","legend":"\u003cp\u003eDispersion patterns of termite dealates. (A) Comparison of the travel distance between different dealate units. The traveled distance for 15 minutes was obtained from the mean traveled distance in 0.2 seconds for each individual. (B) Distribution of dispersed distances from the starting point after 15 min in unwrapped trajectories. Unwrapped trajectories and mean-square displacements in (C) single individuals and (D) tandem leaders. Red regression lines were generated using LMM. Data for females and males are pooled in (B-C).\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6837416/v1/3df63c1527bb013befa3fe68.png"},{"id":84459060,"identity":"ea83045a-1b72-4b83-9102-7191cf87bba0","added_by":"auto","created_at":"2025-06-12 08:31:18","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":81158,"visible":true,"origin":"","legend":"\u003cp\u003eTermite movement simulations. (A) Two different initial searching conditions. Without light, termites are located randomly across the entire area, while with light, termites are located in a specific area. In both situations, the area of \u003cem\u003eL\u003c/em\u003e\u003csub\u003earea\u003c/sub\u003e x \u003cem\u003eL\u003c/em\u003e\u003csub\u003earea\u003c/sub\u003e is a periodic boundary condition. (B) The results of the simulation with \u003cem\u003eL\u003c/em\u003e\u003csub\u003earea\u003c/sub\u003e = 30 m and \u003cem\u003eL\u003c/em\u003e\u003csub\u003elight\u003c/sub\u003e = 3 m. See Figure S4 for other parameter combinations.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6837416/v1/b07a26b01e81fe7604f06b2a.png"},{"id":104739995,"identity":"12e7e542-53b2-4ad9-82ab-9f295228f2ac","added_by":"auto","created_at":"2026-03-16 16:14:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2213498,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6837416/v1/dbcd2231-fcb1-46c0-af84-a9236f140418.pdf"},{"id":84457452,"identity":"bbd7ec26-4823-49a3-b217-b4c4d5decc03","added_by":"auto","created_at":"2025-06-12 08:15:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1736315,"visible":true,"origin":"","legend":"","description":"","filename":"SIJPS.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6837416/v1/bbd8f77eb705c7b484b52285.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluating mate encounter and walking dispersal dynamics of termites using posture tracking and behavioral simulation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAmong more than 3,000 species, some termites are serious structural pests, causing damage of \u003cspan\u003e$\u003c/span\u003e40\u0026nbsp;billion annually across the world, as estimated in 2010 (Rust and Su, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In particular, invasive termite species have a substantial impact; for example, \u003cem\u003eCoptotermes formosanus\u003c/em\u003e is listed as one of the top 10 most costly invasive species (Cuthbert et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Termite studies have traditionally focused on mature colonies, since damage occurs only after colonies reach maturity (Gordon et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Su and Scheffrahn, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). However, even though the mature colony is made up of millions of individuals, all termite colonies begin with a monogamous mating pair of a female and a male (Nutting, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1969\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) with a few exceptions (Perdereau et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This highly mobile mate-pairing stage is a determinant of the initial infestation, population dynamics, and invasion success. Yet, this critical stage has been understudied compared to the mature colonies. In this study, I explore the mate-finding and dispersal dynamics of a termite, \u003cem\u003eCoptotermes formosanus\u003c/em\u003e Shiraki (Blattodea: Heterotermitidae), especially focusing on their walking behaviors.\u003c/p\u003e \u003cp\u003eDuring a particular season, a large number of alates (winged reproductive individuals) fly off from their parental colony nests (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). There are three immediate tasks for alates: 1) dispersal from their original place, 2) finding a mating partner, and 3) finding a nest site to start a colony. This information on \u003cem\u003eC. formosanus\u003c/em\u003e is summarized in a chapter of a book on this species, where dispersal flight is relatively well described (Chouvenc, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The dispersal flight of \u003cem\u003eC. formosanus\u003c/em\u003e initiates at dusk (late twilight) and continues for 15 minutes to an hour (Chouvenc, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Alates of \u003cem\u003eC. formosanus\u003c/em\u003e show a variable ability to disperse during flight. Direct observation recorded dispersal distance up to 460 m (Ikehara, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1966\u003c/span\u003e), and extensive mark recapture efforts showed that they can disperse 621 m on average and up to 1,300 m (Messenger and Mullins, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Mullins et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), while genetic analyses of alates and surrounding colonies suggest alates dispersed 20\u0026ndash;510 m away (Simms and Husseneder, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Collectively, these indicate that alates of \u003cem\u003eC. formosanus\u003c/em\u003e have a decent ability to disperse and expand their distribution ranges and thus are useful for distribution surveys. However, as a socially monogamous insect, females and males of \u003cem\u003eC. formosanus\u003c/em\u003e must find a partner after dispersion and wing shedding. Unlike social Hymenoptera, all important mating processes happen during walking, i.e., finding a mating partner, engaging in pairing courtship, and finding a nest site. Thus, quantifying their post-dispersal movement is essential to understanding mating success.\u003c/p\u003e \u003cp\u003eAfter landing on the ground and shedding their wings, both females and males engage in mate search by walking. This mate search is assumed to be a random search (Mizumoto and Dobata, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), indicating that termites do not know where their partner is until they encounter it, because \u003cem\u003eC. formosanus\u003c/em\u003e termites do not rely on vision (Mizumoto and Bourguignon, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) or long-distance attracting chemicals (Chouvenc et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Raina et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) to locate a partner. Before encountering a partner, both females and males actively search for a partner to maximize the search area (Mizumoto and Dobata, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Once encountered, a female and male pair perform tandem running behavior, with the leader female and the follower male coordinating motion, while searching for a suitable nest site. In tandem running, a female leader determines the course of the movement (Mizumoto et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Valentini et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), whereas the follower males maintain contact with their antennae and pulps (Mizumoto and Reiter, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Raina et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). In case of accidental separation between partners, a female leader pauses to wait for the partner, and a male follower engages in an area-restricted search, which is an effective reunion strategy for the strayed partners (Mizumoto et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mizumoto and Dobata, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Encounters of the same sex may also result in tandem runs (Mizumoto et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024a\u003c/span\u003e), but they are rarer than those of other species (Mizumoto et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Therefore, on the ground, termites dynamically alternate mate and nest searches until they settle in an available and suitable space for colony foundation (Chouvenc, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Su et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e1989\u003c/span\u003e). These observations provide important behavioral information for termite dealates. However, the dispersion-encounter dynamics of dealates remain unknown, e.g., how far termites can travel after shedding their wings or the effective density required for mate searchers to encounter their partner.\u003c/p\u003e \u003cp\u003eIn this study, I address these questions by reanalyzing termite searching strategies studied in a previous study and building a behavioral simulation. Especially, Mizumoto and Dobata \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e studied the movement patterns of termite dealates in both \u003cem\u003eCoptotermes formosanus\u003c/em\u003e and \u003cem\u003eReticulitermes speratus\u003c/em\u003e to investigate their mate searching strategies. This study obtained the movement trajectories of termite dealates in a petri dish arena, by tracking their body centers with a background subtraction technique, i.e., UMATracker (Yamanaka and Takeuchi, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Since then, more video tracking tools have become available, and there have been many advancements in deep learning-based posture tracking. In this study, by updating the analysis, I reanalyze the same video with one of these advanced tools, i.e., SLEAP (Pereira et al., 2022) to track termite movements by body parts. Then, using posture information, I attempted to unwrap termite movements in a dish to the approximate open space to grasp their dispersal abilities by walking. Furthermore, using the movement parameters of termites, I developed a mate searching simulation and tested the effect of density and urban lights on mating encounter dynamics.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003eBehavioral data\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the walking behavior of termite dealates, I used the videos obtained in a previous study (Mizumoto and Dobata, 2019). In this study, experiments with \u003cem\u003eC. formosanus\u003c/em\u003e were performed to study the adaptive mate search strategy used by termites. Alates were collected using light trapping or from two colonies of \u003cem\u003eC. formosanus\u003c/em\u003e nesting wood in Wakayama, Japan in June 2017. After dispersal flights in the lab, termites that shed their wings were used for observations. Observations were performed in a petri dish (\u0026Oslash; = 145 mm) filled with a moistened plaster. They observed termites under two different conditions: in single searching experiments, they introduced a female or a male to the experimental arena and recorded their movement for 30 min, while in tandem running observations, they introduced one female and one male together to the arena and recorded for 60 min. A total of 22 single females, 21 single males, and 20 tandem-running pairs were observed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll videos were analyzed using SLEAP v 1.4.0 (Pereira et al., 2022) to estimate the movement of the body parts of each individual. The model was based on the model developed for \u003cem\u003eC. formosanus\u003c/em\u003e in a previous study (Mizumoto and Reiter, 2025), with a 17-node skeleton capturing key anatomical landmarks: antenna tips (left and right), antenna middles, antenna bases, head (centered at the mouthparts), segmental boundaries (head\u0026ndash;pronotum, pronotum\u0026ndash;mesonotum, metanotum\u0026ndash;abdomen), abdomen tip, and all six legs (fore, mid, and hind; left and right). I only used data from the head and abdominal tip for movement analysis. Owing to the video quality, the detection accuracy of the legs or antennae was very low, but including these improved the tracking accuracy of the head and abdomen tips. I trained a U-Net-based model with a multi-animal top-down approach, with a receptive field size of 76 pixels for the centroid and 316 pixels for the centered instance, on Nvidia GeForce RTX 4090, where augmentation was performed by rotating images from -180 to 180 \u0026deg;. Video analysis was performed for tandem running and single termites separately because of the setup difference between these two experiments, where I finished tandem running first and then used the model developed for tandem running to develop the model for single termites. I labeled 65 frames from 15 videos in tandem running, while 61 frames from 25 videos in single termites. While tracking after inference, the instance similarity method with the greedy matching method was used. All pose estimation data were converted into HDF5 files for further analysis. Python was used to format all HDF5 files for further analysis and convert them into FEATHER files for analysis in R (R Core Team, 2024). We employed a linear interpolation method to address the missing values in the dataset. After scaling all data from pixels to millimeters, we used a median filter with a kernel size of five to reduce noise. All analyses were performed after downsampling at 5 FPS.\u003c/p\u003e\n\u003cp\u003eFrom the trajectories, the following kinetic variables were obtained: First, I determined the body center as the middle position between the head and the abdomen tip. The displacements of the body center positions were computed for every frame to obtain the instantaneous movement speed. The changes in the movement speed (acceleration/deceleration) and movement direction were also computed using the displacements. Independent of the movement direction, the termite heading direction was computed as the vector from the abdominal tip to the head. For tandem running observations, I defined tandem running as a state in which the distance between the female abdominal tip and the male head is shorter than 3.1 mm (Mizumoto and Reiter, 2025), where short separation or short running (\u0026lt; 1 s) was smoothed. Then, I analyzed movement patterns only during tandem running behavior to compare with single dealates.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eUnwrapping movements in a dish to open space\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn the dish arena, termite movements are bounded by the arena wall, making it impossible to investigate their dispersal behavior (Nagaya et al., 2017). In this study, however, to grasp dispersal ability by walking in termite dealates, I converted the movement trajectories recorded in a circular dish into approximated open-space movements by applying a series of corrections to movements bounded by a constrained space. The conversions addressed two main artifacts: wall-following behavior and mismatches between heading and movement directions caused by the dish walls. Note that these conversions do not completely reflect their motion in open space; instead, I aimed to approximate how far termites could disperse if there were no boundaries in a dish (Figure S1-3).\u003c/p\u003e\n\u003cp\u003eFirst, termites in a dish often exhibit a wall-following behavior, moving along the perimeter of the dish in a smooth and curved trajectory (Miramontes et al., 2014; Paiva et al., 2020; Shimoji et al., 2019). I assume that termite movements were biased due to the wall and that termites would maintain their heading direction rather than curving along a dish wall in an open space. Thus, I considered that termites were forced to turn at angles that required them to rotate along the wall. To correct this, the x-y coordinates were converted into polar coordinates relative to the center of the arena. I searched for sequences of frames where termites moved more than 10 mm in the same direction as the angular coordinates. For each of these events, I obtained the number of angles the termite rotated and then adjusted the trajectory by rotating the positions to extend the path outward, unwrapping the wall-following sequences (Figure 2A).\u003c/p\u003e\n\u003cp\u003eSecond, near the wall, termite movements are often bounded by the wall, creating many discrepancies between the heading direction (direction from the abdominal tip to the head) and the actual movement direction. These discrepancies were fixed near the wall (defined as the outer half region in the area) by rotating the trajectory around the previous location to align it with the heading direction. This assumes that the termite attempts to move forward along its body axis without redirection arising from the dish or tracking artifacts (Figure 2B).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistical analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eI used linear mixed models (LMMs) to analyze the speed, speed change, and turning patterns, using the functions lmer() in the package \u0026lsquo;lme4\u0026rsquo; (Bates and Maechler, 2015) and lme() in \u0026lsquo;nlme\u0026rsquo; (Pinheiro, 2011). The likelihood ratio (type II) test was used to examine the statistical significance of each explanatory variable. I investigated the relationship between speed and speed change using an LMM with speed change as the response variable, and speed, unit type (single or tandem leader), and their interaction as fixed effects. Video ID nested within the original colony was included as a random effect (random intercept). A similar LMM tested differences in speed between units, with unit type as the fixed effect. In addition, to compare variability in these parameters between units, I compared two LMMs, one assuming equal variance and another allowing variance to differ between units, using likelihood ratio tests. Also, travel distance was compared using an LMM with travel distance as the response, unit type as a fixed effect, and colony as a random effect. Distance was calculated by summing mean step lengths (every 0.2 s) over 15 minutes for the aid of interpretation.\u003c/p\u003e\n\u003cp\u003eNext, I investigated the dispersal patterns of trajectories unwrapped to simulate open space. For the tandem running observations, I focused on each tandem running event rather than each video, as the latter included both tandem running and separations. First, for each trajectory, the displacements from the beginning points at 15-minute time points were extracted and compared between units using a similar LMM as above. The mean squared displacement (MSD) was computed to investigate the diffusive properties of the unwrapped trajectories. MSD is defined as the average squared distance from the starting point after a delay time \u0026tau;, and follows MSD ~ \u0026tau;\u003csup\u003e\u0026alpha;\u003c/sup\u003e, where \u0026alpha; indicates the diffusion type: \u0026alpha; = 1 for Brownian (normal), \u0026alpha; \u0026lt; 1 for subdiffusive, and \u0026alpha; \u0026gt; 1 for superdiffusive motion (Viswanathan et al., 2011). MSDs were obtained in the entire range of each trajectory, using the function computeMSD() in the package \u0026lsquo;flowcatchR\u0026rsquo; (Marini, 2017). To obtain the diffusion properties, I examined the relationship between MSD and \u0026tau; using a log-log transformation. The fitting was restricted to a subset of datasets (0.2, 0.4, 0.6, 0.8, 1, 2, 4, 6, \u0026hellip;, 1000) to avoid oversampling at a larger \u0026tau;. The fitting was performed using an LMM with each trajectory identity included as a random slope. The slope \u0026alpha; obtained from this regression corresponds to the scaling exponent, which characterizes the diffusion regime (e.g., sub-diffusive, diffusive, or super-diffusive).\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eBoth single dealates and tandem leaders showed a clear correlation between movement speed and change in speed: termites tended to speed up after slower movements and slow down after faster ones (Figure 3AB). However, the slopes of this response differed between the two groups (LMM, interaction: \u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003csub\u003e1\u003c/sub\u003e = 28.18, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), with singles showing more sensitive speed adjustments (slope, single: -0.184, leader: -0.176). Their average speeds did not differ (LMM, \u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003csub\u003e1\u003c/sub\u003e = 1.2, \u003cem\u003eP\u003c/em\u003e = 0.273), but both speed and acceleration were more variable in singles than leaders, as seen in the broader data distributions (Figure 3AB). Models allowing group-specific variances fit the data much better than those assuming equal variance (speed: \u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003csub\u003e1\u003c/sub\u003e = 17010.06, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001; change in speed: \u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003csub\u003e1\u003c/sub\u003e = 21499.91, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), confirming reduced variability in tandem leaders.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe turning patterns showed a similar pattern: singles exhibited broader distribution than tandem leaders (Figure 3CD), supported by model comparison (\u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003csub\u003e1\u003c/sub\u003e = 27673.09, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). Interestingly, the relationship between speed and turning was different between groups. In singles, the turning angles became more variable according to movement speed (Figure 3C). On the other hand, tandem leaders decreased turning angle variabilities when moving steadily, with a local minimum in turning SD around 3.8 mm/0.2 sec (Figure 3D).\u003c/p\u003e\n\u003cp\u003eTermites continued moving throughout the 15-minute observation, despite the bounded arena. Travel distance did not differ significantly between singles and leaders (\u0026chi;\u0026sup2;₂ = 1.52, \u003cem\u003eP\u003c/em\u003e = 0.469; Figure 4A). Notably, termites walked 23 \u0026plusmn; 4.2 m (mean \u0026plusmn; S.D.) in 15 min on average. After applying trajectory unwrapping to project paths into open space (Figure 4CD, Figures S1\u0026ndash;S3), tandem leaders dispersed further than singles (\u0026chi;\u0026sup2;₁ = 5.03, \u003cem\u003eP\u003c/em\u003e = 0.025; Figure 4B): singles dispersed 6.5 \u0026plusmn; 3.7 m from the origin, whereas leaders dispersed 9.6 \u0026plusmn; 4.8 m.\u003c/p\u003e\n\u003cp\u003eThe MSD analysis showed that tandem leaders exhibited more diffusive movement than single termites (Figure 4CD). The estimated diffusive exponent \u0026alpha; was 1.65 (with S.D. of 0.12 by the random slope, LMM) for singles, while 1.80 (with S.D. of 0.12 by the random slope, LMM) in tandem leaders. In either case, the trajectories showed superdiffusive properties, as observed in arthropods in (pseudo-) open spaces (Johnson et al., 1992; Mizumoto et al., 2024b; Nagaya et al., 2017; Seuront and Stanley, 2014).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSimulations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI used an individual-based model to examine the dynamics of termite mating encounters based on empirically estimated movements in open space. Simulations took place within a square area of size \u003cem\u003eL\u003c/em\u003eₐᵣₑₐ \u0026times; \u003cem\u003eL\u003c/em\u003eₐᵣₑₐ under periodic boundary conditions. Two mate-search scenarios were considered (Figure 5A): (i) \u003cem\u003ewithout light\u003c/em\u003e, where all individuals were initially distributed randomly across the entire area, and (ii) \u003cem\u003ewith light\u003c/em\u003e, where individuals were first attracted to a light source before shedding their wings and began their search from a concentrated square region of size \u003cem\u003eL\u003c/em\u003e\u003csub\u003elight\u003c/sub\u003e \u0026times; \u003cem\u003eL\u003c/em\u003e\u003csub\u003elight\u003c/sub\u003e. In both scenarios, females and males moved until they encountered an opposite-sex individual. An encounter was defined as the distance between their centers becoming smaller than \u0026phi; = 10 mm, following Mizumoto and Dobata (2019).\u003c/p\u003e\n\u003cp\u003eIndividuals moved via correlated random walks, with both speed and turning angle correlated across timesteps. Speed at the current timestep was a function of the previous speed, reflecting empirical evidence that acceleration correlates with speed (Figure 3). Speed was updated using the following relationship:\u003c/p\u003e\n\u003cp\u003e\u003cimg width=\"288\" height=\"18\" src=\"data:image/png;base64,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\" alt=\"image\"\u003e,\u003c/p\u003e\n\u003cp\u003ewhere parameter values were obtained by fitting the empirical datasets of solo individuals, \u003cem\u003ea\u003c/em\u003e = -0.184, \u003cem\u003eb\u003c/em\u003e = 0.910, \u0026sigma; = 0.628. Turning angles also followed a Laplace distribution with scale parameter \u0026sigma; = 0.164. I used the Laplace distribution instead of common angular distributions, such as wrapped Cauchy or von Mises distributions, because the empirically observed turning angles were sharply peaked around zero (Figure 3), and the Laplace distribution provided a better fit.\u003c/p\u003e\n\u003cp\u003eEach simulation timestep represented 0.2 seconds, matching the empirical data sampling rate of 5 FPS. Simulations ran for 30 minutes (9,000 steps), and the number of mating encounters was recorded at every step. Initial population sizes were set to 100, 1,000, and 10,000 individuals with a 1:1 sex ratio, corresponding to small, medium, and large swarming events (Chouvenc et al., 2017; Higa and Tamashiro, 1983; Sugio, 2019). The search area was fixed at \u003cem\u003eL\u003c/em\u003eₐᵣₑₐ = 30 m, and when light attraction was present, the concentration area was \u003cem\u003eL\u003c/em\u003e\u003csub\u003elight\u003c/sub\u003e = 3 m. Simulations were implemented in C++ and executed in R using the Rcpp package (Eddelbuettel and Balamuta, 2018). The results of the sensitivity analysis of these parameters are in the supplementary materials (Figure S4).\u003c/p\u003e\n\u003cp\u003eThe simulation results clearly showed the Allee effects on the termite mating encounters as observed in a termite (Kusaka and Matsuura, 2017). At higher densities, more individuals successfully found a mate, and the presence of light greatly increased encounter probability by locally concentrating termites (Figure 5B, S4). With only 100 randomly distributed individuals in a 30 \u0026times; 30 m area, successful encounters were rare, indicating the inefficiency of pure random search. However, when local density increased, encounter rates rose substantially. Notably, even with a limited population (e.g., 100 individuals), light attraction increased encounter rates beyond those seen in larger populations without light (Figure 5).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn termite dealates, walking to search for a mating partner and a suitable nest site is an essential first task after dispersal. The comparison shows that the movement of tandem running pairs (nest site searching) is more diffusive and more stable than the movement of single termites (mate searching). The moving speed of tandem leaders is less variable than that of single termites, and the turning angles are also less variable (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Such a stable and more straight motion by tandem leaders resulted in dispersing more distances from the initial points, even though the total travel distance was not different from single termites (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis behavioral difference between single termites and tandem leaders makes sense from both ultimate and proximate points of view. From an ultimate perspective, more directed motion during tandem running allows pairs to move away from their initial encounter site. Mate searching behavior is mutual search, where both females and males search for each other, and even slow-moving or pausing behavior can achieve a higher encounter rate for one sex (Foffi et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Mizumoto et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Mizumoto and Dobata, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Reynolds, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). On the other hand, in nest-site search, the advantage of moving a greater distance will be higher than in mate search, as the nest-site does not move to find a site searcher. Furthermore, if termite mate searchers are clumped in one location, dispersing from there may be advantageous, as encountering another mate searcher can lead to the interruption of tandem running (Mizumoto et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFrom a proximate perspective, more stable and straight motion of tandem running may be the consequence of movement coordination. The stable and directed movement seen in tandem running may result from the coordination between the leader and the follower. In this behavior, leaders slow down and followers speed up when the distance increases, and vice versa when they are closer (Mizumoto and Bourguignon, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mizumoto and Reiter, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Valentini et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similar speed controls can be observed in ant tandem running (Franks and Richardson, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Mizumoto et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Valentini et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) or different types of movement coordination (e.g., fish (Schaerf et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)). Also, to maintain contact between leaders and followers, the possible movement directions of leaders may have been limited compared to when they are alone, because sharp turns by leaders often result in the interruption of tandem running (Mizumoto et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Valentini et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In this sense, even though tandem running is a simple movement coordination, cooperation between partners can, in turn, affect the pair-level movement patterns.\u003c/p\u003e \u003cp\u003eArtificial light, especially in urban areas, is generally harmful to nocturnal flying insects (Owens et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), e.g., by trapping insects near the light source for a long period and eliminating the time window for other essential activities (Kasai and Hironaka, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, \u003cem\u003eC. formosanus\u003c/em\u003e (and several other termites) might benefit from artificial lights. Termites exhibit a rapid behavioral switch: while alates are attracted to lights, dealates show negative phototaxis soon after shedding their wings (Chouvenc, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Ferreira and Scheffrahn, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Ohmura et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). This reduces the chance of being trapped near lights and suggests that tandem behavior remains unaffected by urban lighting (Mizumoto and Bourguignon, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Previous studies suggest that urban lights should have contributed to their successful invasion processes (Chouvenc, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), which is indirectly supported by the fact that the diurnal flight species, \u003cem\u003eC. testaceus\u003c/em\u003e, is not as invasive as \u003cem\u003eC. formosanus\u003c/em\u003e or \u003cem\u003eC. gestroi\u003c/em\u003e (Scheffrahn et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The simulation results also support this hypothesis. Using empirically observed walking parameters, I show that low densities (e.g., 100 termites in a 30\u0026times;30 m\u0026sup2; area) are insufficient for successful mate encounters by random search, but artificial lights can inflate the encounter rate, comparable to having ten times more individuals in the same area (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, S4). This effect may make small swarming events more productive (Chouvenc et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Higa and Tamashiro, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1983\u003c/span\u003e; Sugio, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and facilitate colony establishment in invasion frontiers, where population sizes are usually limiting.\u003c/p\u003e \u003cp\u003eNote that the unwrapping method is not a perfect approximation of open space movements. It introduces some artifacts, especially when termites make abrupt 180\u0026deg; turns while following the wall. This can be interpreted as that termites attempted to turn in some direction but were constrained by the wall, resulting in a 180\u0026deg; turn. These sharp turns appear in the unwrapped data as large directional changes (Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e-3). While the walls likely influence behavior (Scharf et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). I consider these effects minimal for searching behaviors in termite dealates. Unlike other solitary insects, termites have only a short time window to find a mate and nest site; failure to do so results in death (Chouvenc, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Mizumoto et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). At this stage, searching is the only task for termites, and they remain highly active (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB), consistent with the field observations. Still, further studies will be required to better estimate the termite on-foot dispersal ability, including mark recapture on termite dealates (Mullins et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), or collecting termites using a nest site trap in the field environments (Nkunika, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Su et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e1989\u003c/span\u003e). While caution is necessary when applying this method to non-termite taxa, it may provide useful insights for other pest insects that rely on walking movement, especially in urban settings (Socha and Zemek, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Suchy and Lewis, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMate pairing is a rarely emphasized phase in termite life cycles, yet it is a crucial starting point for colony foundation and varies widely among species (Mizumoto et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Nutting, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1969\u003c/span\u003e). High density is clearly important for \u003cem\u003eCoptotermes\u003c/em\u003e species that use random encounters as a primary method of the pairing process, but this is not always the case in other invasive pest species (Evans et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), especially in Kalotermitidae. For example, \u003cem\u003eCryptotermes brevis\u003c/em\u003e and \u003cem\u003eIncisitermes minor\u003c/em\u003e are two major drywood pest species in the US and are expanding their distributions in urban settings (Lee et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Both of these exhibit tandem running courtship behavior, but the density is much smaller than that of \u003cem\u003eCoptotermes\u003c/em\u003e termites, and \u003cem\u003eI. minor\u003c/em\u003e disperses during the day (Harvey, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1934\u003c/span\u003e; Minnick, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1973\u003c/span\u003e). Furthermore, e.g., \u003cem\u003eCryptotermes domesticus\u003c/em\u003e lacks tandem running behaviors (Huang et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), which should have a distinct pairing process for colony foundation. These drywood termites are one-piece nesting termites that do not move to other nesting materials according to colony development (Abe, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). Thus, selecting a suitable nest site at the time of pairing becomes critical for future colony success. Yet, our knowledge about mate-pairing and nest-site selection in termites remains limited, both in pests and non-pests. Comparative studies across species would be valuable for predicting how termites spread in urban environments.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study is supported by the USDA National Institute of Food and Agriculture, Hatch project number 7007938.\u003c/p\u003e\n\u003ch2\u003eCompeting Interests\u003c/h2\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe datasets and codes generated during the current study are available at GitHub, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/nobuaki-mzmt/DealateDiffusion\u003c/span\u003e\u003c/span\u003e. The accepted version will be deposited in Zenodo to obtain DOI.\u003c/p\u003e\n\u003ch2\u003eEthics approval\u003c/h2\u003e\n\u003cp\u003eThis study did not require ethical approval as it involved only the analysis of previously published data. No new data were collected from human or animal subjects.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eNM is the only author of the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eI thank Dr. Jian Chen for nominating me for the Collection \u0026quot;Emerging Leaders in Pest Science: Celebrating 100 Years of Innovation,\u0026rdquo; and all collaborators relating to the series of projects on termite tandem running behavior. I acknowledge the use of ChatGPT, a language model developed by OpenAI, for minor suggestions with respect to the texts and coding. This study is supported by the USDA National Institute of Food and Agriculture, Hatch project number 7007938.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbe T. 1987. Evolution of life types in termites In: Kawano S, Connell J, Hidaka T, editors. Evolution and Coadaptation in Biotic Communities. Tokyo: University of Tokyo Press. pp. 125\u0026ndash;148.\u003c/li\u003e\n \u003cli\u003eBates DM, Maechler M. 2015. Package \u0026ldquo;lme4\u0026rdquo; Linear Mixed-Effects Models using \u0026ldquo;Eigen\u0026rdquo; and S4. \u003cem\u003eJournal of Statistical Software \u0026middot;\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eChouvenc T. 2025. Invasive termites and their growing global impact as major urban pests. \u003cem\u003eCurrent Opinion in Insect Science\u003c/em\u003e \u003cstrong\u003e69\u003c/strong\u003e:101368. doi:10.1016/j.cois.2025.101368\u003c/li\u003e\n \u003cli\u003eChouvenc T. 2023. 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The Physics of Foraging: An Introduction to Random Searches and Biological Encounters. Cambridge: Cambridge University Press.\u003c/li\u003e\n \u003cli\u003eYamanaka O, Takeuchi R. 2018. UMATracker: An intuitive image-based tracking platform. \u003cem\u003eJournal of Experimental Biology\u003c/em\u003e \u003cstrong\u003e221\u003c/strong\u003e:1\u0026ndash;24. doi:10.1242/jeb.182469\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-pest-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pest","sideBox":"Learn more about [Journal of Pest Science](https://www.springer.com/journal/10340)","snPcode":"10340","submissionUrl":"https://submission.nature.com/new-submission/10340/3","title":"Journal of Pest Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Alate behavior, colony foundation, nest establishment, movement ecology, urban entomology, light pollution, courtship, Formosan subterranean termite","lastPublishedDoi":"10.21203/rs.3.rs-6837416/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6837416/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSeveral termite species are considered problematic as urban structural pests since mature colonies grow to thousands to millions of individuals. Yet, each colony begins with a single mating encounter between a female and a male. After seasonal dispersal flights, termite dealates walk to search for a mating partner and a nest site. This initial stage is critical for dispersal, infestation, and invasion success. However, the search dynamics and success of these walking termites remain poorly understood, especially under varying environmental conditions. In this study, I investigated mate-searching and post-pairing dispersal behaviors in \u003cem\u003eCoptotermes formosanus\u003c/em\u003e, one of the most damaging subterranean termites, by reanalyzing observations in the experimental arena using a deep-learning posture tracking approach. I show that termites can walk an average of 23 m within 15 minutes, with estimated displacements up to 18.74 m. Nest-searching tandem pairs showed more directional and stable motion with higher dispersal potential than mate-searching single termites because of the movement coordination. Simulations parameterized by termite observations showed that urban light attraction greatly contributed to the pairing success of termites, even with a low termite population density. These findings suggest that simple movement rules and environmental cues can enhance mating encounters and dispersal, facilitating infestation and invasion. Comparative behavioral studies across termite species may link the movement ecology of termites with their pest status and invasive potential.\u003c/p\u003e","manuscriptTitle":"Evaluating mate encounter and walking dispersal dynamics of termites using posture tracking and behavioral simulation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-12 08:15:12","doi":"10.21203/rs.3.rs-6837416/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-11T08:02:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-05T14:47:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"254915785506513929124610885676059416175","date":"2025-11-25T04:43:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-12T20:13:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-28T16:51:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"149838141488109885742619189966713787820","date":"2025-06-18T21:41:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"778303836960131956932873404771982613","date":"2025-06-16T12:37:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-10T11:01:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-07T04:51:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-07T04:50:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Pest Science","date":"2025-06-06T13:21:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-pest-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pest","sideBox":"Learn more about [Journal of Pest Science](https://www.springer.com/journal/10340)","snPcode":"10340","submissionUrl":"https://submission.nature.com/new-submission/10340/3","title":"Journal of Pest Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"389a7eea-ebb2-49a0-a62d-73070aa01658","owner":[],"postedDate":"June 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-16T16:09:32+00:00","versionOfRecord":{"articleIdentity":"rs-6837416","link":"https://doi.org/10.1007/s10340-026-02023-3","journal":{"identity":"journal-of-pest-science","isVorOnly":false,"title":"Journal of Pest Science"},"publishedOn":"2026-03-10 16:00:29","publishedOnDateReadable":"March 10th, 2026"},"versionCreatedAt":"2025-06-12 08:15:12","video":"","vorDoi":"10.1007/s10340-026-02023-3","vorDoiUrl":"https://doi.org/10.1007/s10340-026-02023-3","workflowStages":[]},"version":"v1","identity":"rs-6837416","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6837416","identity":"rs-6837416","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}