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. Author manuscript; available in PMC: 2026 Sep 14.
Published in final edited form as: Anim Behav. 2026 Sep 9;240:123702. doi: 10.1016/j.anbehav.2026.123702

Environmental and Genetic Conditions Shaping Monarch Butterfly Migration Biology

Hsiang-Yu Tsai a, Cristian E Molina a, John M Pleasants b, Marcus R Kronforst a
PMCID: PMC13564201  NIHMSID: NIHMS2191468  PMID: 42729918

Abstract

Monarch butterflies in North America migrate south each autumn, but the mechanisms initiating their migratory flight remain unclear. We investigated environmental, developmental, and genetic factors shaping directional flight using three flight simulators: two at ground level (with and without wind blockage) and a novel balloon-based system that lifted butterflies 30 meters into the air. We tested summer and autumn-generation monarchs, as well as summer monarchs reared under autumn-like conditions to assess developmental influences. Autumn-generation monarchs exhibited significant southwestern flight orientation, observed only in the balloon simulator, highlighting the importance of high-altitude flight. Summer monarchs reared under autumn-like conditions displayed southward orientation, larger wings, and partial reproductive diapause, indicating that seasonal cues alone can induce migratory traits. In contrast, a lab-reared monarch lineage maintained in captivity since 2016 showed reduced wing size and impaired orientation, even when raised outdoors in autumn, suggesting a loss of migratory traits without migration. Unexpectedly, many butterflies in the balloon simulator oriented upwind, suggesting wind may serve as a directional cue. These findings reveal key environmental and genetic influences on monarch migration and establish the balloon flight simulator as a valuable tool for studying migratory behaviour, with implications for conservation in a changing climate.

Keywords: Danaus plexippus, behaviour, migration, captive breeding, phenotypic plasticity

Introduction

Migration is a vital strategy used by many animal species to access seasonal resources or track favorable environmental conditions. This complex behaviour depends on the timing of departure, which influences stopover patterns, arrival timing, and ultimately the fitness of migrating individuals (Ramenofsky & Wingfield, 2007; Saino et al., 2011; Schmaljohann et al., 2022).Understanding the triggers that initiate migration is therefore key to understanding how migrants adapt to their environments (Charmantier & Gienapp, 2014; Pulido et al., 2001). The onset of long-distance migration involves two interconnected components: a developmental phase that prepares the organism for migration (Doyle et al., 2022; Liu et al., 2021; Maggini et al., 2022) and a flight strategy that enables navigation through varying environmental conditions (Chapman et al., 2010; Hedenström & Hedh, 2024; Srygley & Dudley, 2008). During development, migrants undergo physiological, morphological (Crossin et al., 2004), and metabolic changes (Weber, 2009) that equip them for sustained long-distance travel, with these traits shaped by genetic and environmental factors. In addition, effective flight strategies allow migrants to respond to dynamic environmental cues such as sun position (Lindecke et al., 2019), wind conditions (Chapman et al., 2010; T. P. Weber & Hedenström, 2000), and temperature (Able, 1973; Guo et al., 2020), ensuring successful navigation and energy efficiency during migration.

Among migratory species, insects are especially numerous, both in terms of biodiversity and ecological significance, serving as important consumers, pollinators and decomposers (Chapman et al., 2015; Satterfield et al., 2020; Wotton et al., 2019). The monarch butterfly (Danaus plexippus) is a well-known migratory insect that is famous for long-distance migration. Unlike many migratory animals, which repeat their migration multiple times, eastern North American monarchs migrate southward only once in their lifetime. In response to seasonal cues, monarchs eclosing in the late summer and autumn embark on a southward journey of up to 4,000 kilometers to their overwintering sites in central Mexico. In spring, these same individuals fly north to the southern United States, where they reproduce and die, with successive generations continuing northward and re-establishing the species’ breeding range (Brower et al., 1977; Reppert & de Roode, 2018; F. Urquhart & Urquhart, 1978). This multi-generational migration precludes the possibility of socially learning the migration route, indicating that this behaviour is genetically encoded.

Migratory monarchs display distinctive traits, including southern-oriented flight in autumn, relatively large forewings, and reproductive diapause (Herman, 1973). Previous studies have explored the environmental cues influencing these traits (Barker & Herman, 1976; Davis & de Roode, 2018; Freedman & Dingle, 2018; Goehring & Oberhauser, 2002; James, 1983; Tenger-Trolander et al., 2019; Tenger-Trolander & Kronforst, 2020; Wilcox et al., 2020), with particular attention placed on factors such as decreasing day length and temperature (Barker & Herman, 1976). Research has also delved into the neural mechanisms underlying migration (Heinze & Reppert, 2011; Reppert et al., 2010) and how monarchs utilize flight strategies to navigate environmental conditions, employing methods such as radio tracking (Fisher et al., 2020; Knight et al., 2019; Wilcox et al., 2020) and vanishing bearings (Calvert, 2001; Perez et al., 1999). However, while considerable progress has been made in understanding the developmental processes that initiate migration, these studies have predominantly focused on the impact of rearing environments, as these are relatively straightforward to manipulate through common garden experiments. Despite recent advances in electronic tagging that are beginning to overcome long-standing tracking limitations, comprehensive investigations into how developmental processes and flight strategies interact to trigger migration remain scarce.

In this study, we addressed two critical aspects of monarch butterfly migration: (1) how genetic background and environmental conditions during development shape the initiation of migration, and (2) how flight strategies—such as directional orientation, altitude preferences, and wind utilization—interact with environmental conditions to facilitate successful migration. To explore these questions, we reared monarch butterflies from summer and autumn generations under both controlled (growth chamber) and outdoor conditions, assessing migration-related traits under varying flight scenarios. Additionally, we tested monarchs from a long-term, lab-reared population to evaluate how multiple captive generations affect migratory behaviour, particularly the retention or loss of directional orientation. Using a novel balloon-based flight simulator alongside ground-based systems, we examined the contributions of environmental and developmental cues to migratory traits.

Our findings emphasize the critical roles of altitude, wind, and seasonal cues in the initiation and maintenance of migration. They also reveal how migratory behaviour diminishes in lab-reared populations over generations. Overall, these findings advance our understanding of the environmental and behavioural mechanisms responsible for monarch migration and inform future research and conservation efforts focused on migratory species.

Materials and Methods

Animal Husbandry

Monarch butterfly caterpillars were collected from the field near Chicago in early June 2023 and housed in mesh pop-up cages (30.5 cm3) with continuous access to their host plant, Asclepias syriaca (common milkweed). To prevent Ophryocystis elektroscirrha (OE) infection, fresh milkweed was collected daily and surface-sterilized using a 1:19 bleach solution before feeding. Once adults eclosed, individuals were screened for OE spores by pressing adhesive tape against the abdomen and examining for spores. Any infected individuals were immediately frozen. OE-free adults were housed in medium-sized mesh cages (91.5 cm × 30.5 cm2), separated by sex, and fed Birds Choice Butterfly Nectar twice daily. These individuals constituted the “wild-caught” generation.

To produce the first captive-bred generation, males and females from the wild-caught group were hand-paired. After mating, females were placed individually into mesh cages with host plants for oviposition. Eggs from each family were divided evenly between two rearing conditions. Half were transferred to a controlled environmental chamber designed to simulate autumn conditions (see details below), producing the “autumn growth chamber” treatment. The remaining eggs were reared outdoors under natural summer conditions at an urban garden site, producing the “summer field generation.” (Fig S1)

Adults from the outdoor summer generation were then hand-paired to produce the “autumn field generation.” These individuals were reared outdoors at Warren Woods Ecological Field Station, a protected natural field site used for both rearing and behavioural testing. The field station consisted of multiple enclosed plots that were flat, open, and free of prominent visual landmarks with natural surrounding vegetation and no artificial nighttime lighting. These conditions provided a natural environment while minimizing confounding visual cues during behavioural experiments. Throughout all stages, adult butterflies were individually labeled and fed Birds Choice butterfly nectar twice daily.

Autumn-like Growth Chamber

To test environmental effects on migration, we reared summer-generation butterflies in a growth chamber under autumn-like conditions. To replicate autumn-like environmental conditions, field temperature data were collected from August 5 to October 1, 2022 using a temperature logger placed at the outdoor field station. Daily average daytime and nighttime temperatures were calculated throughout this period and used to generate day-by-day environmental chamber settings for July 5 to August 31, 2023, along with corresponding daily changes in photoperiod (Table S1).

After early October in the reference dataset, average temperatures dropped below 10 °C, which could compromise survival or behaviour under laboratory conditions. Therefore, beginning September 1, 2023, chamber temperatures were adjusted to maintain conditions conducive to butterfly activity while preserving seasonal realism. Daytime and nighttime temperatures were set to 20.5 °C and 15.7 °C, reflecting the average conditions observed during September of the reference year, while photoperiod continued to decrease incrementally to simulate ongoing seasonal progression. Lighting was provided by dual fluorescent lamps with fixed on/off cycles matched to programmed day length.

Experiments with monarch lab lines

Experiments were also conducted using two long-term laboratory colonies established in 2016 and 2017 and maintained at Iowa State University. Until 2021, both colonies were reared in growth chambers at constant temperature26.6 °C) and long-day photoperiods (16 h light). After 2021, colonies were maintained indoors under ambient temperature and artificial lighting conditions (15h dark: 9 h light). No additional wild-caught monarchs were introduced into either colony after they were established. Colonies were routinely screened for OE infection. A small number of infected individuals were occasionally detected and removed immediately, and all butterflies used in this study were OE free.

In July 2023, eggs from both colonies were shipped to the field station and reared outdoors as separate families using the same protocol as wild-caught caterpillars. Adults were combined to form the “summer lab line” group; however, high mortality due to viral infection prevented behavioural testing. Surviving individuals were paired to generate an autumn cohort, which was supplemented with a second egg shipment received in August 2023. Adults emerging from this combined group formed the “autumn lab line” population used in behavioural assays.

Flight Simulator Methods

Directional flight orientation was measured using three complementary flight-simulator setups. Prior to tethering, thoracic scales were gently removed with transparent tape, and a small adhesive bandage was applied to improve attachment (Parlin et al., 2021). A lightweight fishing line was attached using UV-curing glue, allowing more natural flight and increasing survival rates. Butterflies recovered for at least one day after tethering and were placed outdoors for at least one hour before testing.

We then tested their orientation behaviour in autumn using three flight simulators that mimicked different conditions: (1) ground-level open air, representing natural ground-level flight, (2) ground-level wind block, allowing visual exposure but blocking wind, and (3) a balloon method, in which butterflies ascended to 30 m with full wind exposure (Fig. 1A). Ground-level simulators lacked a height stimulus, whereas the balloon method provided both altitude and wind conditions similar to natural migratory flight.

Figure 1. Monarch butterfly orientation behaviour in field-reared populations across flight simulators.

Figure 1.

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(A) Schematic diagram of the three flight simulators: two open-air ground-level simulators, one with a wind guard, and the balloon flight simulator. The GoPro camera beneath the butterfly records orientation behaviour during flight. (B, C) Orientation plots for Eastern North American monarchs reared in the field, comparing the Summer (B, ground level open air: n = 10, Rayleigh test, P = 0.25; ground level with wind block: n = 19, Rayleigh test, P = 0.2; balloon: n = 18, Rayleigh test, P = 0.39) and Autumn generations (C, ground level open-air: n = 14, Rayleigh test, P = 0.49; ground level with wind block: n = 20, Rayleigh test, P = 0.055, balloon: n = 20, Rayleigh test, P = 0.031) across the three simulators. Each black line indicates the mean flight direction of an individual butterfly (0°–359°), with line length proportional to the strength of directional preference (0–1). The red arrow represents the mean direction and R* calculated by Moore’s Rayleigh test per group. Directions are plotted relative to 0° (north) and 180° (south). The radii of the dashed circles represent the required score of R* for each statistical significance level (from the inner to the outer: P<0.05, P<0.01, P<0.001). Autumn-generation butterflies oriented south only in the balloon flight simulator.

In the “ground-level open-air” flight simulator, butterflies were tethered to a white, horizontal line aligned with true north in an open area without wind obstruction. In the “ground-level windguard” flight simulator, a transparent PVC cylinder (30 cm diameter × 61 cm height) surrounded the butterfly to reduce wind while maintaining visual exposure. In both methods, a GoPro Hero 4 camera (GoPro, Inc) positioned below recorded flight heading and duration.

In the “balloon method,” each butterfly was tethered beneath a 2.1-meter balloon, which was released to a height of 30 meters. This setup allowed the butterfly to fly at a high altitude while interacting with natural wind conditions (D. Gibo, 1986). A GoPro HERO10 Black camera (GoPro, Inc) and an LI-550F TriSonica® weather sensor (LI-COR Environmental), positioned below the butterfly, recorded flight behaviour alongside environmental variables, including wind speed, direction, and temperature (Fig. S4). A Raspberry Pi 4 model B (Raspberry Pi Holdings) connected to the weather sensor served as a data logger for weather metrics. Each test lasted 10 minutes and 30 seconds and was terminated if a butterfly stopped flying for more than 15 seconds. To ensure accurate analysis, the first 30 seconds of each video were excluded, allowing the butterfly time to ascend and stabilize its flight. All experiments were conducted on sunny days between early September and October 2023 at the same field station used for rearing the autumn field generation.

Ovary dissection

To assess reproductive status, all butterflies were frozen post-experiment and female ovaries were dissected. The abdomens of the female butterflies were removed, and a longitudinal cut was made to open the abdomen. An oocyte was classified as mature if it had surface ridges typical of those about to be laid. The number of mature oocytes was counted, and individuals with more than one mature oocyte were considered sexually mature; others were classified as being in reproductive diapause.

Wing scanning

After flight tests, we removed and analyzed the right forewing of each butterfly to measure its area. Photographs of the wings were taken, and the images were converted to binary form. The software ImageJ was then used to calculate wing area.

Wind Data Extraction

Real-time wind conditions were recorded during each flight experiment using two ultrasonic anemometers, a TriSonica weather station mounted near the butterfly at altitude, and a HOBO by Onset S-WCG-M003 Ultrasonic Wind Smart Sensor positioned at ground level. Both sensors sampled wind speed and direction at one-second intervals throughout each trial.

To characterize broader seasonal wind patterns, we also used ERA5-Land reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF). Wind speed and direction were extracted at hourly resolution for sites where we conducted our rearing and behavioural experiments. Three additional sites were selected based on monarch butterfly records from Journey North, a community science program in which citizen scientists report monarch observations. Data were compiled for the month of September to match the timing of behavioural assays.

Data Analysis

Butterfly Flight and Wind Direction

We used DeepLabCut version 2.2, a ResNET-50-based network, to train a tracking model to analyze butterfly heading directions. Five body parts—head, thorax, right forewing, left forewing, and abdomen tip—were labeled in the training videos. The output of the DeepLabCut model provided the coordinates of the five labeled body parts for each frame. To calculate butterfly heading direction per second during the balloon flight simulator trials, we sampled every 60th frame, corresponding to the 60 fps GoPro framerate. For the two ground-level flight simulators, we sampled every 60th or 30th frame depending on the GoPro’s framerate. Only the head and thorax coordinates were used to determine heading direction by subtracting the thorax coordinates from the head coordinates to create the flight vector.

For the two ground-level flight simulators, the butterfly was tethered to a white line oriented toward true north, which served as the reference for the north vector. Heading direction was determined by measuring the angle between the flight vector of the butterfly and the north vector. In the balloon flight simulator, heading direction was recorded using the LI-550F TriSonica weather station attached to the balloon, as the balloon could rotate while floating in the sky. A GoPro camera, aligned with the weather station’s reference direction, captured the flight vector. To calculate the heading direction, we first measured the angle between its flight vector and the long axis of the GoPro’s field of view (represented as the vector (0,1)). This angle was then added to the heading direction recorded by the TriSonica at the corresponding time frame, yielding the final heading direction.

To calculate the average heading direction for each trial, the butterfly’s heading was recorded every 10 seconds. These angular data (in degrees) were converted into Cartesian coordinates using the “Circular” package in RStudio 1.3.959. The mean heading direction (0–359°) and flight consistency (r = 0–1, where higher values indicate greater consistency) were then computed for each butterfly. To determine whether butterflies within each group exhibited significant directional flight, we weighted each individual’s mean flight direction by its consistency score and conducted a non-parametric Moore’s modified Rayleigh test (Moore, 1980). By ranking individuals’ consistency, the test evaluates whether a group of weighted circular data is significantly different from a uniform distribution. The test generates an R* score per group. Larger values of R* represent greater directionality of a group, while smaller values indicate that the flight directions of the group are approaching a random distribution. Confidence intervals for mean direction were estimated by nonparametric bootstrap resampling. Within each treatment, data were resampled with replacement 5,000 times, and the rank-weighted mean direction was recalculated for each bootstrap replicate. The 95% confidence interval was defined by the 2.5% and 97.5% quantiles of the resulting bootstrap distribution.

To analyze the butterflies’ flight behaviour in relation to wind, we calculated the difference between the wind direction and the butterflies’ heading direction on a per-second basis. The distribution of these differences was plotted, and skewness was calculated to assess wind alignment. A negatively skewed distribution (skewness < 0) indicated upwind flight, while a positively skewed distribution (skewness > 0) suggested downwind flight. To evaluate whether the data distribution deviated from uniformity, we applied the Kolmogorov-Smirnov (KS) test. Additionally, to determine whether wind conditions during each test were significantly directional, wind direction was weighted by wind consistency and analyzed using the Moore’s modified Rayleigh test, following the same method applied to the butterflies’ flight direction. The relationship between wind speed and consistency was evaluated using a generalized linear model (GLM).

Reproductive status and wing morphology

We compared physiological and morphological traits across different generations and treatment groups using the Mann-Whitney U test. For reproductive traits, we assessed binary data indicating whether individuals had reached maturity as well as the number of mature oocytes. Wing variables were also analyzed using the Mann-Whitney U test to evaluate differences across groups.

Ethical Note

All butterflies were handled under permits issued by the United States Department of Agriculture. Throughout the study, care was taken to minimize stress to the animals. Butterflies were housed in enclosed yet spacious cages that allowed free movement. Tethering procedures were completed within 5 minutes, and flight tests were limited to 10 minutes. Under all flight simulator designs, butterflies were able to fly naturally.

Results and Discussion

In the summer field generation, butterflies exhibited no significant directional orientation across any flight simulator (ground level open air: σ = 77°, 95% bootstrap confidence interval 19°-164°,n = 10, R* = 0.73, Rayleigh test, P = 0.25; ground level with wind block: σ = 134°, 95% bootstrap confidence interval 67°-199°, n = 19, R* = 0.76, Rayleigh test, P = 0.2; balloon: σ = 222°, 95% bootstrap confidence interval 182°-339°, n = 18, R* = 0.59, Rayleigh test, P = 0.39, Fig 1B), aligning with previous findings that monarchs do not migrate in summer and thus show no directional flight (Green et al., 2024; Tenger-Trolander et al., 2019). In contrast, the autumn field generation, presumed to be migratory, showed strong southwest directionality exclusively in the balloon flight simulator (σ = 238°, 95% bootstrap confidence interval 205°-288°, n = 20, R* = 1.12, Rayleigh test, P = 0.031, Fig 1C). Ground-level simulators, with and without wind blocking, yielded no significant southern orientation (open-air: σ = 134°, 95% bootstrap confidence interval 7°-259°, n = 14, R* = 0.51, Rayleigh test, P = 0.49; wind block: σ = 64°, 95% bootstrap confidence interval 3°-101°, n = 20, R* = 1.02, Rayleigh test, P = 0.055, Fig 1C). These results support existing evidence that high-altitude flight enables monarchs to integrate visual height cues and directional information from the sun, enhancing migratory orientation (Chapman et al., 2015; Urquhart & Urquhart, 1978). Such behaviour is analogous to findings in migratory birds, where high-altitude release after visual orientation results in sustained migratory behaviour (Demong & Emlen, 1978).

In the balloon test, butterflies from the autumn growth chamber treatment exhibited strong directional orientation (mean vector angle = 214°°, 95% bootstrap confidence interval 190°-243°, n = 23, R* = 1.46, Rayleigh test, P = 0.0025; Fig. 2A), indicating that autumn-like developmental conditions effectively prime migratory behaviour. This result has significant implications. While prior studies using static daylength struggled to identify specific conditions triggering migration behaviour (Tenger-Trolander et al., 2019; Tenger-Trolander & Kronforst, 2020), our results show that gradual decreases in day length and temperature are sufficient to induce southern orientation (Schroeder et al., 2020). This highlights the critical role of environmental cues in initiating migratory behaviour.

Figure 2. Orientation behaviour of monarch butterflies reared in autumn-like conditions and the laboratory-maintained autumn generation.

Figure 2.

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(A) Orientation plots of summer generation monarchs reared in a autumn-like growth chamber, tested across three flight simulators. Butterflies oriented south only in the balloon flight simulator, with no significant southern orientation in the ground-level simulators (ground level open-air: n = 8, Rayleigh test, P = 0.29; ground level with wind block: n = 21, Rayleigh test, P = 0.087; balloon: n = 23, Rayleigh test, P =0.0025). (B) Orientation plots of autumn lab line monarch butterflies, which showed only marginally significant southern orientation behaviour in the balloon flight simulator (ground level open-air: n = 14, Rayleigh test, P = 0.32; ground level with wind block: n = 17, Rayleigh test, P = 0.029; balloon: n = 21, Rayleigh test, P = 0.15). Each black line represents the mean flight direction of an individual butterfly (0°–359°), with line length proportional to the strength of directional preference (0–1). The red arrow indicates the mean direction and R* calculated by Moore’s Rayleigh test per group. Orientation is plotted relative to 0° (north) and 180° (south). The radii of the dashed circles represent the required score of R* for each statistical significance level (from the inner to the outer: P<0.05, P<0.01, P<0.001).

For the autumn lab line, southern directional orientation in the balloon simulator was not significant (σ = 198°, 95% bootstrap confidence interval 143°-288°, n = 21, R* = 0.83, Rayleigh test, P = 0.15, Fig 2B), suggesting weakened migratory behaviour after prolonged captive rearing. This diminished orientation, together with reduced immune function and survival reported in lab populations, likely reflects loss of migratory traits over time.

We further examined orientation behaviour using ground-level simulators with autumn growth chamber and autumn lab line populations, both of which displayed no significant southern orientation (autumn growth chamber: ground level open-air: σ = 69°, 95% bootstrap confidence interval 3°-133°, n = 8, R* = 0.7, Rayleigh test, P = 0.29; ground level with wind block: σ = 63°°, 95% bootstrap confidence interval 6°-111°, n = 21, R* = 0.94, Rayleigh test, P = 0.087, Fig 2A; autumn lab line: ground level open-air: σ = 180°, 95% bootstrap confidence interval 96°-282°, n = 14, R* = 0.65, Rayleigh test, P = 0.32; ground level with wind block: σ = 359°, 95% bootstrap confidence interval 315°-38°, n = 17, R* = 1.13, Rayleigh test, P = 0.029, Fig 2B). Consistent with our results with the autumn field generation, these results demonstrate that butterflies do not exhibit migratory orientation at ground level. All statistical conclusions remained unchanged after Benjamini–Hochberg correction (q = 0.1).

Although our study demonstrated that monarchs did not exhibit migratory orientation in the ground-level simulators we tested, it is important to acknowledge that prior research using the traditional fixed-tether monarch flight simulator—a ground-level device enclosed in an opaque cylinder—has shown southern orientation (Guerra et al., 2012, 2012, 2014; Guerra & Reppert, 2013; Merlin et al., 2009; Mouritsen & Frost, 2002; Parlin et al., 2022; Stalleicken et al., 2005; Tenger-Trolander et al., 2019; Tenger-Trolander & Kronforst, 2020; Zhu et al., 2009). Differences in enclosure and tether design may explain the differing results. Notably, participation rates were nearly 100% in the balloon simulator, higher than in both ground-level and traditional simulators, underscoring its utility for assessing insect orientation under natural conditions.

Reproductive status and wing size, both migration-linked traits, were assessed after orientation behavioural tests for all groups (summer lab line, summer field, autumn growth chamber, autumn lab line, autumn field). All females from the summer lab line and summer field groups were reproductively mature (summer field: n = 28, summer lab line: n = 7, Fig. 3A), with a mean of 90 or more mature oocytes per female (summer field: n = 28, 93.4 ± 9.8 SE; summer lab line: n = 7, 148 ± 24 SE, Fig. 3B). In contrast, fewer than 20% of females from the autumn lab line and autumn field groups were reproductively mature (autumn lab line: n = 64, mature ratio = 0.17 ± 0.048 SE; autumn field: n = 41, mature ratio = 0.12 ± 0.052 SE, Fig. 3A). Additionally, mature oocyte counts were significantly lower in these groups than in summer butterflies (autumn lab line: n = 64, 5.56 ± 2 SE oocytes; autumn field: n = 41, 1.44 ± 0.76 SE, Mann–Whitney U test, P < 0.001, Fig 3B), consistent with previous observations that autumn generation, migratory monarchs are in reproductive diapause (Freedman & Dingle, 2018; Herman, 1981; Li et al., 2016; Urquhart, 1960).

Figure 3. Reproductive status and forewing size differ among monarch butterfly treatment groups.

Figure 3.

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(A) Proportion of sexually mature females (summer lab line: n=7; summer field: n = 28; autumn growth chamber: n=39; autumn lab line: n = 64; autumn field: n = 41). and (B) number of mature oocytes in the ovaries of females across five treatment groups: summer lab line, summer field, autumn growth chamber, autumn lab line, and autumn field generation (summer lab line: n=7; summer field: n = 28; autumn growth chamber: n=39; autumn lab line: n = 64; autumn field: n = 41). (C) Forewing area of butterflies across the five treatment groups, with autumn field and autumn growth chamber butterflies generally exhibiting larger forewing areas (summer lab line: n=7; summer field: n = 49; autumn growth chamber: n=26; autumn lab line: n = 114; autumn field: n = 72). The standard error was presented as the error bar. The number of asterisks indicates the level of statistical significance: *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

Interestingly, butterflies reared in the autumn growth chamber treatment exhibited intermediate reproductive traits compared to summer and autumn field females. Although these butterflies had a higher reproductive maturity ratio than autumn field butterflies (autumn growth chamber: n = 39, mature ratio = 0.85 ± 0.059 SE; autumn field: n = 41, mature ratio = 0.12 ± 0.052 SE, Mann–Whitney U test, P < 0.001, Fig. 3A), they stored fewer oocytes than summer females (autumn growth chamber: n = 39, 31.3 ± 4.9 SE; summer field: n = 28, 93.4 ± 9.8 SE, Mann–Whitney U test, P < 0.001, Fig. 3B). This suggests that day length and temperature influence diapause induction, consistent with previous studies (Goehring & Oberhauser, 2002; Iiams et al., 2019; James, 1983). However, additional autumn environmental factors not present in the growth chamber may further regulate reproductive suppression.

We next examined forewing size across all butterfly groups, as larger forewings are typically associated with migratory monarch populations, aiding in long-distance travel (Li et al., 2016). Autumn-generation butterflies raised in the field had significantly larger forewing sizes compared to summer-generation individuals (summer field: n = 49, forewing area = 7.58 ± 0.12 cm2; autumn field: n = 72, forewing area = 8.27 ± 0.12 cm2, Mann–Whitney U test, P < 0.001, Fig. 3C), consistent with their migratory behaviour. Interestingly, butterflies from the autumn growth chamber exhibited even larger forewing areas than the autumn field generation (n = 26, forewing area = 8.97 ± 0.14 cm2, Mann–Whitney U test, P < 0.001, Fig. 3C). However, the lab line monarchs, regardless of season, displayed smaller forewing sizes compared to wild-derived individuals (summer lab line: n = 7, forewing area = 6.9 ± 0.3 cm2, Mann–Whitney U test, P = 0.0013; autumn lab line: n = 114, forewing area = 7.04 ± 0.056 cm2, Mann–Whitney U test, P < 0.001, Fig. 3C). These results suggest that forewing size, a key migration-related trait, is shaped by a combination of environmental and genetic factors, including potential inbreeding effects in captive populations.

The reduced forewing size and orientation behaviour observed in the lab line butterflies are consistent with trends documented in commercially bred monarchs (Tenger-Trolander et al., 2019), which may have been raised in captivity for decades. Commercial populations show smaller wings than wild-derived monarchs and fail to orient south in the autumn, yet they retain phenotypic plasticity related to reproductive diapause (Tenger-Trolander et al., 2019). The similarities between commercial monarchs and our lab line, which has been reared in captivity since 2016/2017, provide insight into the temporal dynamics of migration trait loss under artificial rearing conditions. Furthermore, monarchs naturally dispersed out of North America to locations around the world (Zhan et al., 2014) and many of these populations do not migrate. The trends we have documented in captivity parallel the natural loss of migratory behavior in those non-migratory dispersal populations. For instance, population genomic analyses indicate that these populations experienced founder effects and reduced genetic diversity (Zhan et al., 2014). They also often exhibit smaller wings while retaining seasonal plasticity in female reproduction (Altizer & Davis, 2010; Freedman et al., 2018; Tenger-Trolander et al., 2023), although their directional flight orientation behaviour remains unknown. Together, these demographic and phenotypic similarities suggest that the transition away from long-distance migration may be accompanied by rapid modification of some migratory traits, whereas others remain conserved. Previous studies show that seasonal cues (Chen et al., 2023; Han & Gatehouse, 1991), physiological stress (Jiang et al., 2011) and genetic factors (Chang et al., 2019) influence migration loss, indicating that migratory behaviour is evolutionarily flexible but vulnerable to disruption.

Given that two of our flight simulators were open-air, we examined how butterflies interacted with wind during their flights. Fine-scale wind data were recorded during each experiment, though a sensor failure limited data collection for the ground-level open-air simulator. We calculated angular differences between flight and wind directions, where smaller values indicated wind alignment and larger values indicated upwind flight. Among the autumn growth chamber butterflies tested in the ground-level simulator, the direction differences were uniformly distributed, indicating no significant relationship between flight orientation and wind (skewness = −0.0305, n = 8, KS test, P = 0.231; Fig. 4A). In contrast, in the balloon-based simulators, the distributions of direction differences were negatively skewed across all treatment groups except for the autumn field generation. For the autumn field generation, the angular differences were uniformly distributed, despite the fact that, like the autumn growth chamber group, the butterflies exhibited significant southward orientation. (autumn field generation: skewness = −0.275, n = 20, KS test, P = 0.355; autumn lab line: skewness = −1.31, n = 21, KS test, P < 0.001; autumn growth chamber: skewness = −1.47, n = 23, KS test, P < 0.001; Fig. 4B). Wind speed, however, showed no significant relationship with flight consistency, either overall or within individual rearing groups (GLM; overall: n = 83, P = 0.48; summer field: n = 18, P = 0.55; autumn field: n = 20, P = 0.32; autumn lab line: n = 21, P = 0.54; autumn growth chamber: n = 23, P = 0.80). The upwind tendency in some groups raised the question of whether specific groups exhibit differential sensitivity to wind direction during orientation.

Figure 4. Interaction of migratory butterflies with wind across flight simulators.

Figure 4.

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(A) In the open-air flight simulator at ground level, migratory butterflies showed no significant interaction with wind direction. (skewness = −0.0305, n = 8, P = 0.231). (B) In the balloon flight simulator, butterflies frequently oriented upwind, but the difference between butterfly and wind direction was not statistically significant in the autumn field generation (autumn growth chamber: skewness = −1.47, n = 23, P < 0.001; autumn field generation: skewness = −0.275, n = 20, P = 0.355; autumn lab line: skewness = −1.31, n = 21, P < 0.001). The interaction between the butterfly and wind direction was quantified as the difference between the butterfly’s mean heading and the wind direction during flight tests. Larger differences indicate more pronounced upwind flight, while smaller differences suggest alignment with the wind (tailwind).

To address this, we quantified wind directionality and consistency during each experiment. No significant wind directionality occurred during summer or autumn field tests (summer σ = 342°, P = 0.31; autumn σ = 356°, P = 0.17; Fig. S2A). In contrast, significant northward winds occurred during autumn growth-chamber and lab-line trials (growth chamber σ = 2°, P < 0.001; lab line σ = 346°, P = 0.019; Fig. S2B). Despite this, autumn lab line butterflies did not show strong directional flight, indicating that wind does not drive orientation behaviour. Thus, monarchs actively selected a flight direction that could not be explained by prevailing wind direction alone. This finding reinforces the idea that orientation behaviour is not simply a passive response to wind but rather reflects an internally driven navigational strategy.

Our experiments revealed that while wind and flight direction were independent, many of the butterflies in the balloon method flew into the wind. Upwind flight is unusual for migratory animals, particularly monarch butterflies, which are generally thought to rely on tailwinds for long-distance travel (Knight et al., 2019). To evaluate the broader ecological context of these findings, we examined long-term wind data from the ECMWF. These data revealed that prevailing winds in the Midwest during September—the peak migration period—blow predominantly from the south (Fig. S3). This aligns with previous studies reporting northward winds at migration starting points in southern Canada and the northern United States (Mouritsen Henrik et al., 2013). Taken together, these data suggest that migratory monarchs may initially fly upwind— not necessarily as a consequence of passive wind forcing, but potentially as a strategy for navigation or orientation (Calvert, 2001; Gibo, 1986; Gibo & Pallett, 1979; Reppert et al., 2010). Such behaviour may help them initiate migration or calibrate internal compasses using wind as a stable environmental cue. Ultimately, however, monarchs appear capable of selecting their intended direction of travel, even in the presence of persistent and directional wind.

These results raise questions about how monarchs detect and later exploit favorable winds to sustain their southward journey. Understanding how migratory butterflies integrate wind cues with internal navigation could reveal strategies for balancing orientation accuracy and energy efficiency. Further research is needed to explore how monarchs compensate for adverse winds and maintain their migratory trajectory en route to overwintering sites.

A potential concern in simulator assays is that unintended visual cues could bias orientation, but our results indicate this was not the case. In the ground-based assays, butterflies were tethered along a north–south axis, which could theoretically bias orientation (Franzke et al., 2020). However, flight directions were broadly distributed and generally random. In the balloon assay, light reflections on the balloon could also be suspected as cues. Because visual conditions were identical across treatments, any artifact would affect all groups equally, which was not observed. Instead, summer monarchs were non-directional while autumn monarchs showed strong directional orientation, consistent with established migration biology, and different treatments exhibited distinct responses. These patterns indicate that orientation reflects biological variation rather than apparatus artifacts.

In summary, our findings highlight the complex interplay between environmental cues, physiological traits, and flight strategies in shaping monarch butterfly migration. By employing innovative flight simulator methods, we demonstrated that high-altitude flight conditions elicit strong migratory orientation, suggesting a critical role for visual and wind-related cues at these altitudes. Our results also underscore the influence of developmental conditions on migratory behaviour and associated traits, such as forewing size and reproductive diapause, while emphasizing the rapidity with which some migratory characteristics are lost in sedentary populations. These insights not only advance our understanding of monarch migration but also provide a framework for investigating broader questions about the ecological and evolutionary factors driving animal migration (Gill et al., 2019). Future research should focus on unraveling the mechanisms underlying wind cue detection, the physiological adaptations enabling energy-efficient flight, and the potential genetic basis of migration-related traits. Such efforts will be pivotal for informing conservation strategies as migratory species face increasing environmental challenges (Charmantier & Gienapp, 2014).

Supplementary Material

Supplementary Figures and Table

Acknowledgments

We thank Sheng-Feng Shen for his help designing the balloon flight simulator, Matthias Steinrücken for his assistance with flight data analysis, Vaibhhav Sinha for his help coding on Raspberry Pi, and Keith Bidne for maintaining monarch lab colonies at Iowa State University and providing eggs. We also thank the Molina family for their support with transportation during fieldwork, the staff of the University of Chicago Warren Woods Ecological Field Station for their hospitality, and Trevor Price for comments on the manuscript.

Funding:

This research was supported by NSF grant IOS-1922624 and NIH grant R35 GM131828 to MRK.

Footnotes

Conflict of Interest:

The authors declare no conflict of interest.

Data availability:

Data and code supporting Figs. 1–4 and Fig. S2, Fig. S3 are uploaded as the supplementary material. The source data underlying Fig. S3 is obtained from the ERA5-Land reanalysis dataset in the European Centre for Medium-Range Weather Forecasts (ECMWF).

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Figures and Table
NIHMS2191468-supplement-Supplementary_Figures_and_Table.docx (2.1MB, docx)

Data Availability Statement

Data and code supporting Figs. 1–4 and Fig. S2, Fig. S3 are uploaded as the supplementary material. The source data underlying Fig. S3 is obtained from the ERA5-Land reanalysis dataset in the European Centre for Medium-Range Weather Forecasts (ECMWF).

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