Rearing History, Larval Density, and Larval Developmental Stage Affect Volatile- and Light-Mediated Diel Hiding Behavior in Mythimna unipuncta

Rearing History, Larval Density, and Larval Developmental Stage Affect Volatile- and Light-Mediated Diel Hiding Behavior in Mythimna unipuncta | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Rearing History, Larval Density, and Larval Developmental Stage Affect Volatile- and Light-Mediated Diel Hiding Behavior in Mythimna unipuncta Kaori Shiojiri, Masayoshi Uefune, Jeremy McNeil, Junji Takabayashi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7466594/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Our previous study has shown that plant volatiles and light jointly influence the diel hiding behavior of Mythimna unipuncta larvae using the third instars of the laboratory colony. Here, we investigated the effect of rearing history, larval density, and developmental stage on the diel hiding behavior of M. unipuncta larvae under controlled laboratory conditions. Third-instar larvae from a newly established, field-derived colony exhibited more frequent hiding behavior in the presence of maize volatiles, regardless of the light regime, whereas third-instar larvae from a long-term laboratory colony (> 5 years) showed no change in response to volatiles. Larval density during the second instar also altered responsiveness; low-density cohorts from the new colony exhibited increased hiding in response to volatiles, whereas high-density cohorts exhibited a decrease. Furthermore, developmental stage also influenced behavior. Second instars from the new colony consistently exhibited increased hiding when exposed to volatiles, regardless of light conditions. In contrast, under light condition, the fifth–sixth instars hid more with volatiles than without. Under dark condition, however, they hid less with volatiles than without. Our results demonstrate that diel hiding behavior in M. unipuncta larvae is shaped not only by immediate environmental cues such as light and plant volatiles but also by larval rearing history, social context (density) and the developmental states. This study provides novel insights into the behavioral adaptations underlying diel activity patterns in herbivorous insects. Biological sciences/Ecology Earth and environmental sciences/Ecology Biological sciences/Zoology diel hiding behavior plant volatiles domestication larval density developmental stages Figures Figure 1 Figure 2 Figure 3 Introduction Several vertebrates and invertebrates exhibit diel activity patterns that are classified as nocturnal, diurnal, or crepuscular 1 . These daily activity patterns are governed by endogenous circadian rhythms, which are regulated by a network of interconnected oscillators in the central nervous system and peripheral organs 2 – 3 . Exogenous factors (zeitgebers) play crucial roles in entraining or synchronizing endogenous clocks. The most extensively studied zeitgebers are light cues associated with the light/dark cycle and fluctuations in thermal cycles. However, other environmental cues can also act as zeitgebers. For instance, Levine et al. (2002) demonstrated that the social context, such as being solitary or in a group, influences the locomotor behavior of Drosophila melanogaster adults, with volatile chemical cues from conspecifics contributing to more synchronized behavior in grouped individuals 4 . Our previous studies have underscored the role of host plant volatiles as potential zeitgebers in the nocturnal behavior of insects. Shiojiri et al. (2006) demonstrated that host plant volatiles significantly influenced the nocturnal behavior (hiding in shelters during the daytime) of Mythimna separata larvae 5 . Even at night, the larvae exhibited increased hiding behavior when exposed to daytime volatiles emitted by either undamaged or conspecific-damaged corn plants as oppose to exposure of the respective nighttime volatiles 5 . Observations regarding the effect of host plant volatiles on hiding behavior have also been reported for Mythimna unipuncta and Spodoptera litura 6 . In contrast to M. separata , these noctuid species do not appear to respond directly to host plant volatiles; rather, their behavior is influenced by significant interactions between light and host plant volatiles. These studies support the hypothesis that host plant volatiles act as zeitgebers, influencing the diel periodicity of Noctuidae larval behavior in a species-specific manner. Studies on insect behavior have involved insect colonies reared for multiple generations under laboratory conditions, which may unintentionally influence behavior through artificial selection (e.g.,7–10). The findings reported by Shiojiri et al. (2011) were conducted by using the third instars from a laboratory colony maintained for over five years, suggesting effects of artificial selection in their results 6 . In the present study, therefore, we investigated how the duration and density of larval rearing in the laboratory affect the hiding behavior of M. unipuncta larvae. Furthermore, since the young M. unipuncta larvae feed mostly during the day and hide well among the grass blades, while older larvae are nocturnal 11 , we compared the responses of second instars and fifth-sixth instars to light and host plant volatiles to investigate whether developmental differences affected their hiding behavior. Results Experiment 1: Effects of rearing history (old vs. young colony) The results of the logistic regression analyses from Experiment 1 are presented in Table 1. Given that light did not influence rearing history (rearing history × light: P = 0.2377; rearing history × light × volatiles: P = 0.4144), we disregarded the light factor when analyzing the interaction between rearing history (new vs. old colony) and volatiles (Fig. 1 ). Larvae from the new colony exhibited a significantly higher proportion of hiding behavior in the presence of volatiles (58%) compared to the absence (23%) (χ 2 = 26.0811, df = 1, P < 0.0001, logistic regression analysis) (Fig. 1 ). In contrast, over 60% of the larvae from the old colony exhibited hiding behavior irrespective of the presence or absence of volatiles (63% and 61%, respectively) (χ 2 = 0.0849, df = 1, P = 0.7798, logistic regression analysis) (Fig. 1 ). Experiment 2: Effects of larval density (high vs. low) The results of the logistic regression analyses in Experiment 2 are presented in Table 2. Given that light did not significantly influence larval density (larval density × light: P = 0.4981; larval density × light × volatiles: P = 0.6254), we disregarded the light factor when analyzing the interaction between larval density and volatiles (Fig. 2 ). Although the differences were not statistically significant, larvae from the low-density colony tended to exhibit a higher proportion of hiding behavior in the presence of volatiles (59%) compared to their absence (23%) (χ 2 = 1.2944, df = 1, P = 0.2553; logistic regression analysis) (Fig. 2 ). In contrast, the larvae from the high-density colony tended to show a lower proportion of hiding behavior in the presence of volatiles (40%) than in their absence (50%) (χ2 = 2.0238, df = 1, P = 0.1549; logistic regression analysis) (Fig. 2 ). These contrasting responses to the presence or absence of light were significantly different between low- and high-density conditions (larval density × volatiles: P = 0.0357) (Table 2). Experiment 3: Effects of larval stadium (second vs. fifth–sixth) The results of the logistic regression analyses from Experiment 3 are presented in Table 3. Given that the interaction between larval age, light, and volatiles was significant ( P = 0.0031), we divided the results into two groups: the second instar group (Fig. 3 A) and the fifth–sixth instar group (Fig. 3 B), to emphasize the interaction between light and volatiles. In the second instar group, the proportion of hiding behavior was significantly higher in larvae exposed to volatiles compared to those not exposed, irrespective of light conditions (under light conditions: 54% with volatile exposure and 36% without; under dark conditions: 56% with volatile exposure and 34% without) (light: χ 2 = 3.2916; df = 1, P = 0.0696; dark: χ 2 = 4.9312, df = 1, P = 0.0264; logistic regression analysis) (Fig. 3 A). In the fifth–sixth instar group, the proportion of hiding behavior was significantly higher in larvae exposed to volatiles under light conditions compared to those not exposed (exposed: 88%; not exposed: 60%) (χ 2 = 10.6177, df = 1, P = 0.0011, logistic regression analysis). In contrast, under dark conditions, the proportion of hiding behavior in larvae exposed to volatiles was significantly lower than that of those not exposed (exposed: 38%; not exposed: 58%) (χ 2 = 4.0338, df = 1, P = 0.0446, logistic regression analysis) (Fig. 3 B). Discussion In Experiment 1, the significant interaction between rearing history and volatiles (Table 1) indicated differing effects of volatiles on the proportions of hiding behavior between the new and old colonies. The proportions of hiding behavior in the new colony were significantly affected by volatiles, whereas those in the old colony were not. These results suggest that the duration of rearing under laboratory conditions (that is, level of domestication) altered the volatile-mediated hiding behavior of M. unipuncta larvae. Domestication may reduce the sensitivity of M. unipuncta larvae to plant volatiles through habituation or genetic adaptation. The effects of domestication on the behavioral and physiological performance of laboratory-reared and wild insects have been previously reported. Richerson and Cameron (1974) examined pheromone release in both laboratory-reared and wild gypsy moths, Lymantria dispar : unlike wild females, laboratory-reared females showed no diel periodicity in pheromone emission and released only very small amounts of pheromone 7 . Grayson et al. (2015) reported that laboratory strains of the gypsy moth, Lymantria dispar which had been continuously reared since 1967, exhibited enhanced traits, such as faster development, shorter diapause, and greater fecundity 8 . Pérez et al. (2018) found that males of Bactrocera tryoni from old colonies released more volatiles during sexual calling than those from young colonies 9 . Lee et al. (2024) reported that domesticated L. dispar larvae displayed reduced sensitivity to predation risk cues from predatory wasps 10 . In Experiment 2, although the effects of volatiles under low- and high-density conditions were not individually significant, the interaction between larval density and volatiles was significant (Table 2, P = 0.0357), indicating that the effect of volatiles on hiding behavior differed significantly between the low- and high-density groups. It is interesting to note that a relatively short exposure to different densities, limited to the second instar stage, was sufficient to induce changes in the volatile-mediated nocturnal behavior of M. unipuncta larvae. In a previous study that reported the effects of density on the performance or behavior of insects, the duration of density exposure was relatively long. Hill and Hirai (1986) reported a positive relationship between pupal weight and fecundity in M. separata and M. pallens , which varied with larval rearing density (singly or in groups of 50–200 larvae after the second or third stadium until the final stadium) 12 . Under field conditions, Lance et al. (1986) found that in low-density populations of L. dispar , larvae fed at night and spent the day resting in sheltered areas away from the canopy 13 . Conversely, in high-density populations, larvae remained in the canopy throughout the day and night, with increased daytime feeding as the population density increased. Levine et al. (2002) demonstrated that living in groups or in isolation for 2 weeks influenced circadian rhythms in D. melanogaster , and that olfactory signals likely mediated these social cues 4 . In Experiment 3, the hiding behaviors mediated by the interaction between light and volatiles differed significantly between the second instars and the fifth–sixth instars (larval age × light × Volatiles, P = 0.0032; Table 3). Young M. unipuncta larvae feed both day and night, whereas older larvae feed primarily at night, hiding at the base of plants or beneath the grass canopy during the day 7 . However, the results of Experiment 3 showed that the second instars used plant volatiles in their hiding behavior under both light and dark conditions. The proportion of hiding behavior in the fifth–sixth instars exposed to volatiles was higher than that in those not exposed under light conditions. In contrast, the reverse was true for dark conditions in the fifth–sixth instars. Shiojiri et al. (2006) reported a similar response: volatiles from corn plants under dark conditions increased the hiding behavior of third instar M. separata , whereas those under light conditions decreased it, irrespective of the light conditions of the larvae 5 . It is expected that the volatiles emitted by corn plants under light and dark conditions may differ qualitatively and/or quantitatively (e.g., 14). Such differences may influence the differential hiding behavior of M. unipuncta larvae in different stages, particularly between second and fifth-sixth instars. Shiojiri et al. (2011) reported that plant volatiles and light act as zeitgebers for the hiding behavior of M. unipuncta , and Spodoptera litura larvae 6 . The present study provides new insights into the hiding behavior of M. unipuncta , demonstrating that it is further modulated by zeitgebers identified in this study, namely, rearing history, larval density, and larval age. Since this study was conducted under laboratory conditions, further is needed to assess how these findings affect the nocturnal behavior of M. unipuncta larvae under field conditions. Materials and Methods Insects and plants Mythimna unipuncta (Lepidoptera: Noctuidae) larvae were maintained in the laboratory for more than five years on an artificial pinto bean diet (modified after Shorey and Hale, 1965) (hereafter referred to as the old colony). Upon emergence, females were placed individually in plastic cages (16 cm diameter, 8 cm height) and fed daily with an 8% sucrose solution. Rearing conditions were kept at 25 ± 0.5°C and 65 ± 5% relative humidity, under a photoperiodic regime of LD 16:8 h, with a light intensity of approximately 1000 lux during the photophase. To examine the potential effects of rearing history on the hiding behavior of M. unipuncta larvae, individuals were collected from fields in Ontario, Canada, and reared for one generation under the same conditions (hereafter referred to as the new colony). Potted corn plants ( Zea mays L. cv. Royal Dent), with three plants per pot, were grown in a controlled-environment growth chamber. The chamber was maintained at 25 ± 2°C and operated on a 16-hour light/8-hour dark photoperiod. All experiments were conducted using 10-day-old plants at the time of testing. Bioassays Bioassays were designed to isolate and evaluate the factors influencing the hiding behavior of M. unipuncta larvae. Both intrinsic (colony history, larval density, and age) and extrinsic (light conditions and plant volatile compounds) factors were considered. As the larvae from the new colony showed distinct hiding behavior in response to volatiles (whereas the larvae from the old colony did not) in Experiment 1, we only used larvae from the new colony in Experiments 2 and 3. One M. unipuncta larva was placed in a plastic cup measuring 10 cm in diameter and 6 cm in height. The cup contained a four-fold filter paper shelter (25 cm²) and a 7 g piece of artificial diet. A 5 × 5 cm nylon gauze window was placed on the top of the cup to allow ventilation (observation arena). Five racks, each with a plastic tray containing ten observation arenas, were placed in the upper part of an incubator at 25 ± 0.5°C and 65 ± 5% relative humidity. The lower plat of the incubator, we placed four pots of corn plants (two plants per pot) to expose the larvae to uninfested corn plant volatiles. For light conditions (approximately 1000 lux), we used corn plants at the beginning of light regime, and for dark condition, we used ones at the beginning of the dark regime. The larvae were kept under either light or dark condition for six hours. After the exposure, we observed the larvae to determine whether they were hiding in the shelters. For the rearing history experiments, the third instars from old and new colonies were used. For the larval density experiments, the second instars from the new colony were reared at two different densities: high density (approximately 0.2 larvae/cm³) and low density (approximately 0.02 larvae/cm³), until they reached the third instar. For the age experiments, we used the second and the fifth–sixth instars from the new colony. Statistics Data from the experiments were analyzed using three-way logistic regression analysis in JMP version 14.2.0 15 . This method was used to assess the impact of multiple factors and their interactions on the hiding behavior of M. unipuncta larvae. The proportions of hiding behavior in the presence and absence of volatiles were compared using one-way logistic regression analysis in JMP. Significance levels were set at p < 0.05 for all statistical tests. The raw data have been included as supplementary material. Declarations Acknowledgments We would like to thank Dr. Rika Ozawa for her comments on the experiments. Authors' contributions Kaori Shiojiri (KS) and Jeremy McNeil designed the study. KS conducted experiments. Junji Takabayashi (JT) and Masayoshi Uefune (MU) conducted statical analysis. JK and KS wrote the original draft. MU revised the draft. Funding This work was supported by Grant-in-Aid for Transformative Research Areas JSPS KAKENHI Grant Numbers 22H00425 and 23H02140 to Kaori Shiojiri and Junji Takabayashi, and 23H04970 to Kaori Shiojiri. Conflicts of interest/Competing interests We have no conflicts of interest Ethics approval Not applicable Consent to participate Not applicable Consent for publication Not applicable Availability of data statement Not applicable Code availability Not applicable References Saunders, D.S., Steel, C.G.S., Valopoulou, X.& Lewis, E.D. (2002) Insect clocks. 3rd ed. Amsterdam: Elsevier Science. Giebultowicz, J.M. (1999) Insect circadian clocks: is it all in their heads? J Insect Physiol. 45, 791-800. https://doi.org/10.1016/S0022-1910(99)00055-4 Giebultowicz, J.M. (2000) Molecular mechanism and cellular distribution of insect circadian clocks. Annu Rev Entomol. 45, 769-793. https://doi.org/10.1146/annurev.ento.45.1.769 Levine, J. D., Funes, P., Dowse, H.B. & Hall, J.C. (2002) Resetting the circadian clock by social experience in Drosophila melanogaster. Science. 298. 2010-2012. DOI: 10.1126/science.1076008 Shiojiri, K., Ozawa, R., & Takabayashi, J. (2006) Plant volatiles, rather than light, determine the nocturnal behavior of a caterpillar. PLoS Biology. 4. e164. https://doi.org/10.1371/journal.pbio.0040164 Shiojiri, K., McNeil, J.N. & Takabayashi, J. (2011) Do host plant volatiles influence the diel periodicity of caterpillar foraging of all species attacking the same host plant. J. Plant Interact. 6, 121-123. https://doi.org/10.1080/17429145.2011.557307 Richerson, J.V. & Cameron, E.A. (1974) Differences in pheromone release and sexual behavior between laboratory-reared and wild gypsy moth adults. Environ Entomol. 3, 475-481. https://doi.org/10.1093/ee/3.3.475 Grayson, K.L.et al. (2015) Performance of wild and laboratory-reared gypsy moth (Lepidoptera: Erebidae): a comparison between foliage and artificial diet. Environ. Entomol. 44, 864–873. https://doi.org/10.1093/ee/nvv063 Pérez, J, Park, S. J. & Taylor, P.W. (2018) Domestication modifies the volatile emissions produced by male Queensland fruit flies during sexual advertisement. Sci. Rep. 8, 16503. DOI:10.1038/s41598-018-34569-3 Lee, Z.A., Baranowski, A.K., Cohen, C.B. Pelletier, T.S. & Preisser, E.L. (2024) Domestication reduces caterpillar response to auditory predator cues. Environ. Entomol. 53, 587–593. https://doi,org/10.1093/ee/nvae040 Hueppelsheuser, T.H. (2018) True armyworm ( Mythimna unipuncta ). Ministry of Agriculture, Britixh Columbia. Hill, M.G. & Hirai K. (1986) Adult responses to larval rearing density in Mythimna separata and Mythimna pallens (Lepidoptera: Noctuidae). Appl. Entomol. Zool. 21, 191-202. https://doi.org/10.1303/aez.21.191 Lance, D.R., Elkinton, J.S. & Schwalbe C.P. (1986) Behaviour of late-instar gypsy moth larvae in high and low density populations. Ecol. Entomol. 12, 267-273. https://doi.org/10.1111/j.1365-2311.1987.tb01005.x Chamberlain, K., Khan, Z.R., Pickett, J.A., Toshova T. & Washams, L. J . (2006) Diel Periodicity in the Production of Green Leaf Volatiles by Wild and Cultivated Host Plants of Stemborer Moths, Chilo partellus and Busseola fusca . J Chem Ecol, 32, 565–577. https://doi-org.kyoto-u.idm.oclc.org/10.1007/s10886-005-9016-5 SAS Institute (2018). JMP Version 14.2.0. Cary, NC: SAS Institute, Inc. Tables Additional Declarations No competing interests reported. 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13:39:15","extension":"html","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":61011,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7466594/v1/f9785d3295f000fca4973390.html"},{"id":91718688,"identity":"ab7abfeb-1712-436e-92c1-4a57bf028222","added_by":"auto","created_at":"2025-09-19 13:47:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":44136,"visible":true,"origin":"","legend":"\u003cp\u003eThe proportion of hidden individuals of the third instar of \u003cem\u003eM. unipuncta\u003c/em\u003e with and without volatiles in the new colony or old colony.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7466594/v1/8f1029e687a51896bfa35090.png"},{"id":91717974,"identity":"b3db4164-1970-4657-accc-9c219e02f446","added_by":"auto","created_at":"2025-09-19 13:39:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":45021,"visible":true,"origin":"","legend":"\u003cp\u003eThe proportion of hidden individuals of the third instar of \u003cem\u003eM. unipuncta\u003c/em\u003e with and without volatiles under low-density or high-density conditions.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7466594/v1/8f29f8b8717f1e8a5f492f53.png"},{"id":91718689,"identity":"14321c61-6e80-4495-a870-cc19e92bc13e","added_by":"auto","created_at":"2025-09-19 13:47:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":52663,"visible":true,"origin":"","legend":"\u003cp\u003eThe proportion of hidden individuals of the second instar (A) or the fifth–sixth instars (B) of \u003cem\u003eM. unipuncta \u003c/em\u003ewith and without volatiles under light or dark conditions.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7466594/v1/ffb6e324d616d957cbd1cc2a.png"},{"id":91720874,"identity":"433e05fa-6c51-4583-abe6-8aca29c0a6f8","added_by":"auto","created_at":"2025-09-19 14:11:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":747611,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7466594/v1/ff147f66-9b37-45be-afe2-6a49e110858b.pdf"},{"id":91717972,"identity":"8519d922-8770-42c5-9824-93ad4d3f8743","added_by":"auto","created_at":"2025-09-19 13:39:15","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":12543,"visible":true,"origin":"","legend":"","description":"","filename":"Data250826.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7466594/v1/fa28177ea8c9730720783b7e.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Rearing History, Larval Density, and Larval Developmental Stage Affect Volatile- and Light-Mediated Diel Hiding Behavior in Mythimna unipuncta","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSeveral vertebrates and invertebrates exhibit diel activity patterns that are classified as nocturnal, diurnal, or crepuscular \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. These daily activity patterns are governed by endogenous circadian rhythms, which are regulated by a network of interconnected oscillators in the central nervous system and peripheral organs \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Exogenous factors (zeitgebers) play crucial roles in entraining or synchronizing endogenous clocks. The most extensively studied zeitgebers are light cues associated with the light/dark cycle and fluctuations in thermal cycles. However, other environmental cues can also act as zeitgebers. For instance, Levine et al. (2002) demonstrated that the social context, such as being solitary or in a group, influences the locomotor behavior of \u003cem\u003eDrosophila melanogaster\u003c/em\u003e adults, with volatile chemical cues from conspecifics contributing to more synchronized behavior in grouped individuals \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOur previous studies have underscored the role of host plant volatiles as potential zeitgebers in the nocturnal behavior of insects. Shiojiri et al. (2006) demonstrated that host plant volatiles significantly influenced the nocturnal behavior (hiding in shelters during the daytime) of \u003cem\u003eMythimna separata\u003c/em\u003e larvae \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Even at night, the larvae exhibited increased hiding behavior when exposed to daytime volatiles emitted by either undamaged or conspecific-damaged corn plants as oppose to exposure of the respective nighttime volatiles \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Observations regarding the effect of host plant volatiles on hiding behavior have also been reported for \u003cem\u003eMythimna unipuncta\u003c/em\u003e and \u003cem\u003eSpodoptera litura\u003c/em\u003e \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. In contrast to \u003cem\u003eM. separata\u003c/em\u003e, these noctuid species do not appear to respond directly to host plant volatiles; rather, their behavior is influenced by significant interactions between light and host plant volatiles. These studies support the hypothesis that host plant volatiles act as zeitgebers, influencing the diel periodicity of Noctuidae larval behavior in a species-specific manner.\u003c/p\u003e\u003cp\u003eStudies on insect behavior have involved insect colonies reared for multiple generations under laboratory conditions, which may unintentionally influence behavior through artificial selection (e.g.,7\u0026ndash;10). The findings reported by Shiojiri et al. (2011) were conducted by using the third instars from a laboratory colony maintained for over five years, suggesting effects of artificial selection in their results \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. In the present study, therefore, we investigated how the duration and density of larval rearing in the laboratory affect the hiding behavior of \u003cem\u003eM. unipuncta\u003c/em\u003e larvae. Furthermore, since the young \u003cem\u003eM. unipuncta\u003c/em\u003e larvae feed mostly during the day and hide well among the grass blades, while older larvae are nocturnal \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, we compared the responses of second instars and fifth-sixth instars to light and host plant volatiles to investigate whether developmental differences affected their hiding behavior.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eExperiment 1: Effects of rearing history (old vs. young colony)\u003c/h2\u003e\u003cp\u003eThe results of the logistic regression analyses from Experiment 1 are presented in Table\u0026nbsp;1. Given that light did not influence rearing history (rearing history \u0026times; light: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.2377; rearing history \u0026times; light \u0026times; volatiles: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.4144), we disregarded the light factor when analyzing the interaction between rearing history (new vs. old colony) and volatiles (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Larvae from the new colony exhibited a significantly higher proportion of hiding behavior in the presence of volatiles (58%) compared to the absence (23%) (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;26.0811, df\u0026thinsp;=\u0026thinsp;1, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, logistic regression analysis) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In contrast, over 60% of the larvae from the old colony exhibited hiding behavior irrespective of the presence or absence of volatiles (63% and 61%, respectively) (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.0849, df\u0026thinsp;=\u0026thinsp;1, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.7798, logistic regression analysis) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eExperiment 2: Effects of larval density (high vs. low)\u003c/h3\u003e\n\u003cp\u003eThe results of the logistic regression analyses in Experiment 2 are presented in Table\u0026nbsp;2. Given that light did not significantly influence larval density (larval density \u0026times; light: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.4981; larval density \u0026times; light \u0026times; volatiles: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.6254), we disregarded the light factor when analyzing the interaction between larval density and volatiles (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Although the differences were not statistically significant, larvae from the low-density colony tended to exhibit a higher proportion of hiding behavior in the presence of volatiles (59%) compared to their absence (23%) (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;1.2944, df\u0026thinsp;=\u0026thinsp;1, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.2553; logistic regression analysis) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In contrast, the larvae from the high-density colony tended to show a lower proportion of hiding behavior in the presence of volatiles (40%) than in their absence (50%) (χ2\u0026thinsp;=\u0026thinsp;2.0238, df\u0026thinsp;=\u0026thinsp;1, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1549; logistic regression analysis) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These contrasting responses to the presence or absence of light were significantly different between low- and high-density conditions (larval density \u0026times; volatiles: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0357) (Table\u0026nbsp;2).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eExperiment 3: Effects of larval stadium (second vs. fifth–sixth)\u003c/h3\u003e\n\u003cp\u003eThe results of the logistic regression analyses from Experiment 3 are presented in Table\u0026nbsp;3. Given that the interaction between larval age, light, and volatiles was significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0031), we divided the results into two groups: the second instar group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA) and the fifth\u0026ndash;sixth instar group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), to emphasize the interaction between light and volatiles. In the second instar group, the proportion of hiding behavior was significantly higher in larvae exposed to volatiles compared to those not exposed, irrespective of light conditions (under light conditions: 54% with volatile exposure and 36% without; under dark conditions: 56% with volatile exposure and 34% without) (light: χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;3.2916; df\u0026thinsp;=\u0026thinsp;1, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0696; dark: χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;4.9312, df\u0026thinsp;=\u0026thinsp;1, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0264; logistic regression analysis) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). In the fifth\u0026ndash;sixth instar group, the proportion of hiding behavior was significantly higher in larvae exposed to volatiles under light conditions compared to those not exposed (exposed: 88%; not exposed: 60%) (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;10.6177, df\u0026thinsp;=\u0026thinsp;1, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0011, logistic regression analysis). In contrast, under dark conditions, the proportion of hiding behavior in larvae exposed to volatiles was significantly lower than that of those not exposed (exposed: 38%; not exposed: 58%) (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;4.0338, df\u0026thinsp;=\u0026thinsp;1, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0446, logistic regression analysis) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn Experiment 1, the significant interaction between rearing history and volatiles (Table\u0026nbsp;1) indicated differing effects of volatiles on the proportions of hiding behavior between the new and old colonies. The proportions of hiding behavior in the new colony were significantly affected by volatiles, whereas those in the old colony were not. These results suggest that the duration of rearing under laboratory conditions (that is, level of domestication) altered the volatile-mediated hiding behavior of \u003cem\u003eM. unipuncta\u003c/em\u003e larvae. Domestication may reduce the sensitivity of \u003cem\u003eM. unipuncta\u003c/em\u003e larvae to plant volatiles through habituation or genetic adaptation. The effects of domestication on the behavioral and physiological performance of laboratory-reared and wild insects have been previously reported. Richerson and Cameron (1974) examined pheromone release in both laboratory-reared and wild gypsy moths, \u003cem\u003eLymantria dispar\u003c/em\u003e: unlike wild females, laboratory-reared females showed no diel periodicity in pheromone emission and released only very small amounts of pheromone \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Grayson et al. (2015) reported that laboratory strains of the gypsy moth, \u003cem\u003eLymantria dispar\u003c/em\u003e which had been continuously reared since 1967, exhibited enhanced traits, such as faster development, shorter diapause, and greater fecundity \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. P\u0026eacute;rez et al. (2018) found that males of \u003cem\u003eBactrocera tryoni\u003c/em\u003e from old colonies released more volatiles during sexual calling than those from young colonies \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Lee et al. (2024) reported that domesticated \u003cem\u003eL. dispar\u003c/em\u003e larvae displayed reduced sensitivity to predation risk cues from predatory wasps \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn Experiment 2, although the effects of volatiles under low- and high-density conditions were not individually significant, the interaction between larval density and volatiles was significant (Table\u0026nbsp;2, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0357), indicating that the effect of volatiles on hiding behavior differed significantly between the low- and high-density groups. It is interesting to note that a relatively short exposure to different densities, limited to the second instar stage, was sufficient to induce changes in the volatile-mediated nocturnal behavior of \u003cem\u003eM. unipuncta\u003c/em\u003e larvae. In a previous study that reported the effects of density on the performance or behavior of insects, the duration of density exposure was relatively long. Hill and Hirai (1986) reported a positive relationship between pupal weight and fecundity in \u003cem\u003eM. separata\u003c/em\u003e and \u003cem\u003eM. pallens\u003c/em\u003e, which varied with larval rearing density (singly or in groups of 50\u0026ndash;200 larvae after the second or third stadium until the final stadium) \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Under field conditions, Lance et al. (1986) found that in low-density populations of \u003cem\u003eL. dispar\u003c/em\u003e, larvae fed at night and spent the day resting in sheltered areas away from the canopy \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Conversely, in high-density populations, larvae remained in the canopy throughout the day and night, with increased daytime feeding as the population density increased. Levine et al. (2002) demonstrated that living in groups or in isolation for 2 weeks influenced circadian rhythms in \u003cem\u003eD. melanogaster\u003c/em\u003e, and that olfactory signals likely mediated these social cues \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn Experiment 3, the hiding behaviors mediated by the interaction between light and volatiles differed significantly between the second instars and the fifth\u0026ndash;sixth instars (larval age \u0026times; light \u0026times; Volatiles, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0032; Table\u0026nbsp;3). Young \u003cem\u003eM. unipuncta\u003c/em\u003e larvae feed both day and night, whereas older larvae feed primarily at night, hiding at the base of plants or beneath the grass canopy during the day \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. However, the results of Experiment 3 showed that the second instars used plant volatiles in their hiding behavior under both light and dark conditions. The proportion of hiding behavior in the fifth\u0026ndash;sixth instars exposed to volatiles was higher than that in those not exposed under light conditions. In contrast, the reverse was true for dark conditions in the fifth\u0026ndash;sixth instars. Shiojiri et al. (2006) reported a similar response: volatiles from corn plants under dark conditions increased the hiding behavior of third instar \u003cem\u003eM. separata\u003c/em\u003e, whereas those under light conditions decreased it, irrespective of the light conditions of the larvae \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. It is expected that the volatiles emitted by corn plants under light and dark conditions may differ qualitatively and/or quantitatively (e.g., 14). Such differences may influence the differential hiding behavior of \u003cem\u003eM. unipuncta\u003c/em\u003e larvae in different stages, particularly between second and fifth-sixth instars.\u003c/p\u003e\u003cp\u003eShiojiri et al. (2011) reported that plant volatiles and light act as zeitgebers for the hiding behavior of \u003cem\u003eM. unipuncta\u003c/em\u003e, and \u003cem\u003eSpodoptera litura\u003c/em\u003e larvae \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. The present study provides new insights into the hiding behavior of \u003cem\u003eM. unipuncta\u003c/em\u003e, demonstrating that it is further modulated by zeitgebers identified in this study, namely, rearing history, larval density, and larval age. Since this study was conducted under laboratory conditions, further is needed to assess how these findings affect the nocturnal behavior of \u003cem\u003eM. unipuncta\u003c/em\u003e larvae under field conditions.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eInsects and plants\u003c/h2\u003e\u003cp\u003e\u003cem\u003eMythimna unipuncta\u003c/em\u003e (Lepidoptera: Noctuidae) larvae were maintained in the laboratory for more than five years on an artificial pinto bean diet (modified after Shorey and Hale, 1965) (hereafter referred to as the old colony). Upon emergence, females were placed individually in plastic cages (16 cm diameter, 8 cm height) and fed daily with an 8% sucrose solution. Rearing conditions were kept at 25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u0026deg;C and 65\u0026thinsp;\u0026plusmn;\u0026thinsp;5% relative humidity, under a photoperiodic regime of LD 16:8 h, with a light intensity of approximately 1000 lux during the photophase. To examine the potential effects of rearing history on the hiding behavior of \u003cem\u003eM. unipuncta\u003c/em\u003e larvae, individuals were collected from fields in Ontario, Canada, and reared for one generation under the same conditions (hereafter referred to as the new colony).\u003c/p\u003e\u003cp\u003ePotted corn plants (\u003cem\u003eZea mays\u003c/em\u003e L. cv. Royal Dent), with three plants per pot, were grown in a controlled-environment growth chamber. The chamber was maintained at 25\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C and operated on a 16-hour light/8-hour dark photoperiod. All experiments were conducted using 10-day-old plants at the time of testing.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eBioassays\u003c/h3\u003e\n\u003cp\u003eBioassays were designed to isolate and evaluate the factors influencing the hiding behavior of \u003cem\u003eM. unipuncta\u003c/em\u003e larvae. Both intrinsic (colony history, larval density, and age) and extrinsic (light conditions and plant volatile compounds) factors were considered. As the larvae from the new colony showed distinct hiding behavior in response to volatiles (whereas the larvae from the old colony did not) in Experiment 1, we only used larvae from the new colony in Experiments 2 and 3.\u003c/p\u003e\u003cp\u003eOne \u003cem\u003eM. unipuncta\u003c/em\u003e larva was placed in a plastic cup measuring 10 cm in diameter and 6 cm in height. The cup contained a four-fold filter paper shelter (25 cm\u0026sup2;) and a 7 g piece of artificial diet. A 5 \u0026times; 5 cm nylon gauze window was placed on the top of the cup to allow ventilation (observation arena). Five racks, each with a plastic tray containing ten observation arenas, were placed in the upper part of an incubator at 25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u0026deg;C and 65\u0026thinsp;\u0026plusmn;\u0026thinsp;5% relative humidity. The lower plat of the incubator, we placed four pots of corn plants (two plants per pot) to expose the larvae to uninfested corn plant volatiles. For light conditions (approximately 1000 lux), we used corn plants at the beginning of light regime, and for dark condition, we used ones at the beginning of the dark regime. The larvae were kept under either light or dark condition for six hours. After the exposure, we observed the larvae to determine whether they were hiding in the shelters.\u003c/p\u003e\u003cp\u003eFor the rearing history experiments, the third instars from old and new colonies were used. For the larval density experiments, the second instars from the new colony were reared at two different densities: high density (approximately 0.2 larvae/cm\u0026sup3;) and low density (approximately 0.02 larvae/cm\u0026sup3;), until they reached the third instar. For the age experiments, we used the second and the fifth\u0026ndash;sixth instars from the new colony.\u003c/p\u003e\n\u003ch3\u003eStatistics\u003c/h3\u003e\n\u003cp\u003eData from the experiments were analyzed using three-way logistic regression analysis in JMP version 14.2.0 \u003csup\u003e15\u003c/sup\u003e. This method was used to assess the impact of multiple factors and their interactions on the hiding behavior of \u003cem\u003eM. unipuncta\u003c/em\u003e larvae. The proportions of hiding behavior in the presence and absence of volatiles were compared using one-way logistic regression analysis in JMP. Significance levels were set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for all statistical tests. The raw data have been included as supplementary material.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Dr. Rika Ozawa for her comments on the experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKaori Shiojiri (KS) and Jeremy McNeil designed the study. KS conducted experiments. Junji Takabayashi (JT) and Masayoshi Uefune (MU) conducted statical analysis. JK and KS wrote the original draft. \u0026nbsp;MU revised the draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Grant-in-Aid for Transformative Research Areas JSPS KAKENHI Grant Numbers 22H00425 and 23H02140 to Kaori Shiojiri and Junji Takabayashi, and 23H04970 to Kaori Shiojiri.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest/Competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe have no conflicts of interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSaunders, D.S., Steel, C.G.S., Valopoulou, X.\u0026amp; Lewis, E.D. (2002) Insect clocks. 3rd ed. Amsterdam: Elsevier Science. \u003c/li\u003e\n\u003cli\u003eGiebultowicz, J.M. (1999) Insect circadian clocks: is it all in their heads? J Insect Physiol. 45, 791-800. https://doi.org/10.1016/S0022-1910(99)00055-4\u003c/li\u003e\n\u003cli\u003eGiebultowicz, J.M. (2000) Molecular mechanism and cellular distribution of insect circadian clocks. Annu Rev Entomol. 45, 769-793. https://doi.org/10.1146/annurev.ento.45.1.769\u003c/li\u003e\n\u003cli\u003eLevine, J. D., Funes, P., Dowse, H.B. \u0026amp; Hall, J.C. (2002) Resetting the circadian clock by social experience in Drosophila melanogaster. Science. 298. 2010-2012. DOI: 10.1126/science.1076008\u003c/li\u003e\n\u003cli\u003eShiojiri, K., Ozawa, R., \u0026amp; Takabayashi, J. (2006) Plant volatiles, rather than light, determine the nocturnal behavior of a caterpillar. PLoS Biology. 4. e164. https://doi.org/10.1371/journal.pbio.0040164\u003c/li\u003e\n\u003cli\u003eShiojiri, K., McNeil, J.N. \u0026amp; Takabayashi, J. (2011) Do host plant volatiles influence the diel periodicity of caterpillar foraging of all species attacking the same host plant. J. Plant Interact. 6, 121-123. https://doi.org/10.1080/17429145.2011.557307\u003c/li\u003e\n\u003cli\u003eRicherson, J.V. \u0026amp; Cameron, E.A. (1974) Differences in pheromone release and sexual behavior between laboratory-reared and wild gypsy moth adults. Environ Entomol. 3, 475-481. https://doi.org/10.1093/ee/3.3.475\u003c/li\u003e\n\u003cli\u003eGrayson, K.L.et al. (2015) Performance of wild and laboratory-reared gypsy moth (Lepidoptera: Erebidae): a comparison between foliage and artificial diet. Environ. Entomol. 44, 864\u0026ndash;873. https://doi.org/10.1093/ee/nvv063\u003c/li\u003e\n\u003cli\u003eP\u0026eacute;rez, J, Park, S. J. \u0026amp; Taylor, P.W. (2018) Domestication modifies the volatile emissions produced by male Queensland fruit flies during sexual advertisement. Sci. Rep. 8, 16503. DOI:10.1038/s41598-018-34569-3\u003c/li\u003e\n\u003cli\u003eLee, Z.A., Baranowski, A.K., Cohen, C.B. Pelletier, T.S. \u0026amp; Preisser, E.L. (2024) Domestication reduces caterpillar response to auditory predator cues. Environ. Entomol. 53, 587\u0026ndash;593. https://doi,org/10.1093/ee/nvae040\u003c/li\u003e\n\u003cli\u003eHueppelsheuser, T.H. (2018) True armyworm (\u003cem\u003eMythimna unipuncta\u003c/em\u003e). Ministry of Agriculture, Britixh Columbia.\u003c/li\u003e\n\u003cli\u003eHill, M.G. \u0026amp; Hirai K. (1986) Adult responses to larval rearing density in \u003cem\u003eMythimna separata\u003c/em\u003e and \u003cem\u003eMythimna pallens \u003c/em\u003e(Lepidoptera: Noctuidae). Appl. Entomol. Zool. 21, 191-202. https://doi.org/10.1303/aez.21.191\u003c/li\u003e\n\u003cli\u003eLance, D.R., Elkinton, J.S. \u0026amp; Schwalbe C.P. (1986) Behaviour of late-instar gypsy moth larvae in high and low density populations. Ecol. Entomol. 12, 267-273. https://doi.org/10.1111/j.1365-2311.1987.tb01005.x\u003c/li\u003e\n\u003cli\u003eChamberlain, K., Khan, Z.R., Pickett, J.A., Toshova T. \u0026amp; Washams, L. J \u003cem\u003e.\u003c/em\u003e (2006) Diel Periodicity in the Production of Green Leaf Volatiles by Wild and Cultivated Host Plants of Stemborer Moths, \u003cem\u003eChilo partellus\u003c/em\u003e and \u003cem\u003eBusseola fusca\u003c/em\u003e . J Chem Ecol, 32, 565\u0026ndash;577. https://doi-org.kyoto-u.idm.oclc.org/10.1007/s10886-005-9016-5\u003c/li\u003e\n\u003cli\u003eSAS Institute (2018). JMP Version 14.2.0. Cary, NC: SAS Institute, Inc.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cimg 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\" 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Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"diel hiding behavior, plant volatiles, domestication, larval density, developmental stages","lastPublishedDoi":"10.21203/rs.3.rs-7466594/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7466594/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOur previous study has shown that plant volatiles and light jointly influence the diel hiding behavior of \u003cem\u003eMythimna unipuncta\u003c/em\u003e larvae using the third instars of the laboratory colony. Here, we investigated the effect of rearing history, larval density, and developmental stage on the diel hiding behavior of \u003cem\u003eM. unipuncta\u003c/em\u003e larvae under controlled laboratory conditions. Third-instar larvae from a newly established, field-derived colony exhibited more frequent hiding behavior in the presence of maize volatiles, regardless of the light regime, whereas third-instar larvae from a long-term laboratory colony (\u0026gt;\u0026thinsp;5 years) showed no change in response to volatiles. Larval density during the second instar also altered responsiveness; low-density cohorts from the new colony exhibited increased hiding in response to volatiles, whereas high-density cohorts exhibited a decrease. Furthermore, developmental stage also influenced behavior. Second instars from the new colony consistently exhibited increased hiding when exposed to volatiles, regardless of light conditions. In contrast, under light condition, the fifth\u0026ndash;sixth instars hid more with volatiles than without. Under dark condition, however, they hid less with volatiles than without. Our results demonstrate that diel hiding behavior in \u003cem\u003eM. unipuncta\u003c/em\u003e larvae is shaped not only by immediate environmental cues such as light and plant volatiles but also by larval rearing history, social context (density) and the developmental states. This study provides novel insights into the behavioral adaptations underlying diel activity patterns in herbivorous insects.\u003c/p\u003e","manuscriptTitle":"Rearing History, Larval Density, and Larval Developmental Stage Affect Volatile- and Light-Mediated Diel Hiding Behavior in Mythimna unipuncta","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-19 13:39:10","doi":"10.21203/rs.3.rs-7466594/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-02T11:24:25+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-09T02:15:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"325111114224851677767776138482590775619","date":"2025-11-28T15:21:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-17T22:06:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"45660285595124535234452476468395800747","date":"2025-09-15T16:37:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-13T16:34:18+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-05T11:52:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-02T08:54:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-30T08:40:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-08-27T00:21:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"88a4e3e1-0414-4dca-9b7f-4b443843ce74","owner":[],"postedDate":"September 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":54962911,"name":"Biological sciences/Ecology"},{"id":54962912,"name":"Earth and environmental sciences/Ecology"},{"id":54962913,"name":"Biological sciences/Zoology"}],"tags":[],"updatedAt":"2026-03-04T17:08:23+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-19 13:39:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7466594","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7466594","identity":"rs-7466594","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}