Next Article in Journal
Effect of Bt-Cry1Ab Maize Commercialization on Arthropod Community Biodiversity in Southwest China
Previous Article in Journal
Two New Species of Mesochorista (Insecta, Mecoptera, Permochoristidae) from the Guadalupian Yinping Formation of Chaohu, Eastern China
Previous Article in Special Issue
Toxicity Profiling Validates Trajectory Modeling for Identifying Sogatella furcifera Migration Sources in Southern China
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Insects
Volume 16
Issue 11
10.3390/insects16111131
insects-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Dispersal Ecology of the Beet Armyworm in the Florida Panhandle: Implications for Outbreaks and Insecticide Resistance Spread

by
Eduardo Soares Calixto
1,*,
João Gabriel Tardin de Moraes
1,
Ethan Carter
2,
Isaac L. Esquivel
3 and
Silvana V. Paula-Moraes
4,*
1
West Florida Research and Education Center, Department of Entomology and Nematology, University of Florida, Jay, FL 32565, USA
2
IFAS Extension Jackson County Office, University of Florida, Marianna, FL 32448, USA
3
Department of Entomology & Nematology, North Florida Research and Education Center, Institute of Food and Agricultural Services, University of Florida, Quincy, FL 32351, USA
4
Department of Entomology, University of Nebraska-Lincoln, Lincoln, NE 68583, USA
*
Authors to whom correspondence should be addressed.
Insects 2025, 16(11), 1131; https://doi.org/10.3390/insects16111131
Submission received: 24 September 2025 / Revised: 27 October 2025 / Accepted: 3 November 2025 / Published: 5 November 2025
(This article belongs to the Special Issue Travelers on the Wind: Migratory Insects as Emerging Research Models)
Browse Figures
Review Reports Versions Notes

Simple Summary

The beet armyworm is an insect pest that feeds on many different crops, including peanuts and vegetables, and it has become more difficult to control because some populations are no longer affected by common insecticides. Knowing where these insects come from and how they move is important to reduce crop losses and improve control strategies. In this study, we tracked beet armyworm populations in peanut fields in two counties in the Florida Panhandle during the 2024 growing season. We collected caterpillars and adult moths using traps and also used a chemical marker found in rainwater to help identify where the moths originated. We found that beet armyworm was present only during July and August, making up about seven percent of all insects collected. The eastern county had more moths than the western county. Results showed that most beet armyworms likely came from South Florida, the Caribbean, or the southern United States, moving northward during the season. These findings improve our understanding of beet armyworm movements and will help farmers and scientists better forecast outbreaks and develop more effective and sustainable ways to manage this pest.

Abstract

Beet armyworm (BAW), Spodoptera exigua (Hübner), is a polyphagous and migratory lepidopteran pest that causes damage to a broad range of host plants, including row crops and vegetables, with increasing reports of insecticide-resistant populations. Understanding its movement ecology is essential for integrated pest management (IPM) and insect resistance management (IRM) programs. We investigated the population dynamics and migratory origins of BAW during the 2024 cropping season in two counties of the Florida Panhandle, USA. Larval sampling and adult pheromone trapping were conducted in commercial peanut fields, and hydrogen stable isotopes were used to infer the probable geographic origins of moths. Across the season, the presence of BAW accounted for 7.1% of all individuals collected, with infestation occurring only in July and August. Moth captures were significantly higher in the eastern Florida panhandle than in the western Florida Panhandle. Stable isotope analysis revealed four distinct migratory patterns, with most BAW likely originating from South Florida, the Caribbean, or the central and southern United States, indicating northward movement. Our findings provide critical insights into the movement ecology of BAW and highlight its implications for outbreak forecasting, resistance management, and regional IPM/IRM strategies in the southeastern United States.

1. Introduction

Beet armyworm (BAW), Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae), is a polyphagous and migratory agricultural pest with a worldwide distribution [1,2,3]. This pest damages leaves, buds, flowers and fruits of vegetables and crops such as peanut, cotton, soybean, tomato, and corn [4,5]. Historically, before the widespread adoption of transgenic Bt cotton in the United States, BAW was recognized as a major cotton pest, causing significant economic losses [6,7]. Today, it remains a key pest of non-Bt crops such as peanut, soybean, and tomato [4,5]. Its high reproductive potential, multivoltine life cycle, and ability to persist in tropical and subtropical regions contribute to local outbreaks and regional dispersal [8].
Chemical control remains the main strategy for BAW management in non-Bt crops [9]. However, frequent insecticide applications, including sprays targeting other pests in other host crops, promote BAW exposure and have led to widespread resistance [9,10,11,12]. This species has evolved resistance to multiple classes of insecticides, including carbamate, avermectin, pyrethroid, organophosphate, benzoylphenylurea, endosulfan, spinosyn, and diamide [9,10,12,13,14,15,16,17]. For instance, diamides are highly effective against lepidopteran pests, but resistance in BAW has been detected in the Florida Panhandle [9,12,17]. Although BAW has historically been a secondary pest in peanut, recent outbreaks in the southern USA, including Georgia and Florida, have caused severe defoliation and raised concerns about insecticide efficacy.
These outbreaks might be closely tied to the movement ecology of BAW, which plays a critical role in linking local pest population surges to the regional spread of insecticide resistance. This species frequently migrates over long distances, with combined abundance monitoring and meteorological analyses indicating that individuals can travel approximately 3500 km from Central Asia to Denmark within about two weeks [18,19]. Migration drives rapid gene flow and can homogenize geographically distant populations, facilitating the spread of insecticide resistance alleles once they arise in local hotspots. In the southeastern USA, the Florida Panhandle and Gulf Coast serve as overwintering refuges, with northward spring migration likely contributing to seasonal infestations in peanut, soybean, and other crops [20]. Understanding the occurrence and movement ecology of BAW in the Florida Panhandle is therefore essential for both outbreak forecast and insecticide resistance management (IRM) on a regional scale. In addition, it can also be used for predicting BAW risk to northern latitudes during the crop season, improving the timing of pest monitoring and insecticide adoption.
In this study, we documented the flight phenology and probability of origin of BAW during the crop season in the Florida Panhandle, USA. Larval scouting was performed in commercial peanut fields, and moths were trapped using a commercial formulation of sex pheromone. The study was conducted on the west and east sides of the Florida Panhandle, in the Santa Rosa (west side) and Jackson (east side) counties, approximately 200 miles apart. Hydrogen stable isotopes were used as biogeochemical markers to infer the probability of origin of the collected individuals [21,22,23]. Overall, our results contribute to a better understanding of the movement ecology of BAW in the Florida Panhandle, an important overwintering region [6,20] and a key hub for the movement of multiple crop pests to northern latitudes in the southeastern USA [22,23,24,25].

2. Materials and Methods

2.1. Larval and Moth Sampling

Larvae were sampled with a beating tray, from 7 June to 21 August 2024, in four peanut fields in Santa Rosa County (latitude and longitude of field 1: 30.771553, −87.141925; field 2: 30.7798856, −87.1427537; field 3: 30.8242651, −87.0568868; field 4: 30.9519779, −87.0627766). These fields were selected to provide representative coverage of peanut production within the county, and the sampling period encompasses much of the peanut crop season in the region, representing a good cover of the county. In each field, five sampling points were established, each at least 20 m from field edges and other sampling points. Each field was treated as an independent replicate. Larvae were collected on 10 sampling dates in field 1 and 6 sampling dates in fields 2, 3, and 4. Larvae were collected and identified to species.
To monitor seasonal peaks in moth abundance, green bucket traps containing pheromone lures (TRÉCÉ Pherocon beet armyworm (BAW) lures, GL/TR-3210-25, Great Lakes IPM, Vestaburg, MI, USA) were installed 1.5 m above ground, at least 100 m apart, across Santa Rosa (west side) and Jackson (east side) counties in the Florida Panhandle. Traps were checked one or two times per week, and lures were replaced every 4 weeks. In Santa Rosa County, four traps were placed at the West Florida Research and Education Center (30.772987, −87.139373), and in Jackson County, 1–2 traps were installed at the four fields (30.943936, −85.427858; 30.883368, −85.505939; 30.798775, −85.069406; 30.950063, −85.144000). Traps in Santa Rosa County were installed on 20 June 2024 and removed on 4 September 2024, whereas traps in Jackson County were installed on 10 July 2024 and removed on 21 August 2024. Host crops in both locations were mainly represented by soybean, peanut, and cotton. Because trap inspections were conducted at varying intervals (one or two times per week), moth captures were standardized as the number of insects per trap per day for each sampling date. All moth specimens were stored at −20 °C until further analysis. To evaluate if the number of BAW moths captured in the sex pheromone trapping per day was different between the west and east sides of the Florida Panhandle, we used a Generalized Linear Mixed-Effects Model (GLMM) with the number of moths per trap per day as the response variable, county as the fixed effect, and trap ID as the random effect. The model was fit using the glmmTMB package [26], Wald χ2 test results were obtained using the car package [27], and estimated marginal means were computed with the emmeans package [28].

2.2. Stable Hydrogen Isotopes Analysis

We selected a subsample of 26 moths for hydrogen isotope analysis, 13 from each side of the Florida Panhandle (Table 1), distributed across the data collection. The right forewing of each moth was removed, processed, and analyzed for hydrogen isotopic ratios. The procedure involved brushing wing scales with a fine paintbrush and cleaning the wings with 70% ethanol to remove surface oils, following the methods of Paula-Moraes et al. [22] and Calixto and Paula-Moraes [23]. This approach is consistent with the traditional 2:1 chloroform–methanol wash [29] and has been validated by Calixto and Paula-Moraes [23]. Once dried, the wings were cut into small pieces and analyzed for hydrogen isotopes at the Stable Isotope Mass Spec Lab, University of Florida, Gainesville, FL, USA. Samples and standards were measured using a Thermo Electron DeltaV Plus isotope ratio mass spectrometer (Thermo Fisher Scientific, Waltham, MA, USA) connected to a ConFlo IV interface and a TCEA (high-temperature conversion elemental analyzer). After being weighed and placed into 4 mm x 6 mm silver capsules, samples were stored in 96-well plates for 48 h to ensure isotopic consistency with the standards [30]. Two keratin standards (CBS and KHS) were used to determine nonexchangeable hydrogen.
After loading the capsules into a Zero Blank autosampler at 1400 °C, hydrogen isotopic values (δ2H) were measured using a Picarro L2120-I isotopic liquid water and water vapor analyzer (Picarro, Santa Clara, CA, USA), which was connected to a Picarro A0211 high-precision vaporizer and a CTC HTS PAL autosampler (Picarro, Santa Clara, CA, USA). Measurement precision was determined using USGS42, yielding a value of 2.99‰ (N = 11). To standardize the results, two internal water standards from the University of Florida (UW Antarctic water and Lake Tulane water) were used, both calibrated against international standards (USGS49 and USGS50). Isotopic values are reported in standard delta notation relative to Vienna Standard Mean Ocean Water. Further details on the methodology are available in Paula-Moraes et al. [22] and Calixto and Paula-Moraes [23].

2.3. Inferences on the Probability of Origin

The probability of origin for each moth was determined following the methodology outlined in Ma et al. [31] using the package assignR in the R software version 4.3.1 [32]. First, we used hydrogen isotope values from amount-weighted, growing-season precipitation at a 5 arc-minute resolution to build an isoscape encompassing a geographic area from 10° N to 50° N latitude and 130° W to 50° W longitude, covering North America as well as parts of the Caribbean and Central America. Then, this isoscape was calibrated using known hydrogen isotope values obtained from published literature to establish the relationship between environmental hydrogen isotopes (e.g., from rainfall) and those in wing tissue (calibration equation: y = −56.14 + 0.61x, R2 = 0.73). Finally, the probability of each sample originating from different locations within the isoscape was assessed, and the average distance and direction of potential origins were calculated. Dispersal direction and distance were estimated using the wDist function, which calculates weighted distances and bearings between each sample’s collection site and potential origin locations based on posterior probability surfaces. To define likely origin regions, we applied a probability threshold, extracting the 10% (90% confidence interval) of grid cells with the highest posterior probability for each sample using the qtlRaster function. Details of inferences on the probability of origin of moths can be found in Calixto and Paula-Moraes [23].

3. Results

3.1. Larvae Recovered

A total of 70 larvae were recovered from the peanut sampling (Figure 1). Larvae of BAW were detected only in July and August, with four larvae collected in July (12.1%) and one in August (2.8%) (Figure 2). Other larvae, such as Spodoptera frugiperda (fall armyworm, FAW), occurred only in July (15.2%). Anticarsia gemmatalis (velvet bean caterpillar, VBC) and Chrysodeixis includens (soybean looper, SBL) were the predominant species, accounting for 41.4% and 37.1% of all larvae, respectively (Figure 1). Larval abundance was highest in July, driven primarily by SBL (36.4%) and VBC (30.3%), and peaked again in August with VBC representing 52.8% of all larvae (Figure 2). Only one S. ornithogalli (yellow-striped armyworm, YAW) was collected in June, and the species remained at low abundance throughout the season. Overall, the larval density per field was low, with 0.4 ± 0.7 (mean ± standard deviation) BAW per field, 0.4 ± 1 FAW per field, 2.2 ± 2.3 SBL per field, 2.4 ± 5.4 VBC per field, and 0.4 ± 0.7 YAW per field.

3.2. Pheromone Trapping

Significant difference in the number of BAW moths captured in the sex pheromone trapping per day was detected between the west and east sides of the Florida Panhandle (χ2 = 21.92, df = 1, p < 0.001; Figure 3). Average captures were 4.53 times higher in Jackson County (east) (11.02 ± 1.53 SE) compared to Santa Rosa County (west) (2.43 ± 1.02 SE). Temporal trends showed consistently high captures in Jackson County throughout July and August, whereas Santa Rosa County exhibited lower and more variable captures, peaking on 30 July 2024 with 6.2 ± 1.6 SE moths per trap per day (Figure 3).

3.3. Probability of Origin

We identified four distinct patterns in the probability of origin for BAW when using hydrogen isotopes (Figure 4 and Figure S1–S3). The first pattern, observed in five samples (19.2% out of 26 samples), suggests a potential origin in the Gulf of California, northwestern Mexico, or the Caribbean region (Figure 4a). Rose diagram bars indicate movement from the southwest (Figure 5a and Figure S4), with an average distance of 2056 ± 52 km (mean ± SD) and an average bearing of 39 ± 15° (Table S1, Figure S5). The second pattern, represented by seven samples (26.9%), indicates a higher probability of origin in South Florida, the Caribbean, and the Gulf of California (Figure 4b and Figure S1–S3) compared to Pattern 1. The average bearing for the probability of origin is 350 ± 3°, suggesting potential movement from the south and southeast (Table S1, Figure S5), with an average distance of 1651 ± 100 km (Figure 5b and Figure S4).
The third pattern, which includes most of the samples (12, 46.1%, Figures S1–S3), shows a high probability of origin in the southern USA and the Caribbean region, particularly in South Florida and the Caribbean (Figure 4c). The average distance from the probable origin of the moths is 1243 ± 16 km (Figure 5c and Figure S4), with an average bearing of 27 ± 7° (Table S1, Figure S5), suggesting movement primarily from the west and southwest. However, some potential movement from the southeast is also indicated by the rose diagram (Figure 4c and Figure S4). Finally, one sample represents a fourth pattern, suggesting a high probability of origin in the central and southern USA, with lower probabilities in South Florida and most of the Caribbean region (Figure 4d and Figure S3). The distance from the probable origin is 1263 km (Figure 5d and Figure S4), with a bearing of 125° (Table S1, Figure S5). Although this direction suggests movement from the southeast, the high probability of origin in central and southern USA states also indicates the possibility of a southward movement (Figure 4d and Figure 5d).

4. Discussion

Understanding the movement ecology of agricultural pests is crucial for predicting and forecasting outbreaks, promoting timely pest detection, management tactic adoption, and ultimately enhancing crop yields. Our study provides novel insights into the seasonal occurrence and potential migratory patterns of BAW in the Florida Panhandle. This region is in the northwestern portion of the state and is recognized as a key overwintering area and source of migratory moths for the southeastern USA [6,20,33].
Across the crop season, we collected a total of 70 larvae in peanut fields, representing five pest species, with BAW accounting for only a minor component of the larval community. Larvae of BAW were detected exclusively in July and August, coinciding with the mid-season of peanut and soybean production in the region. Although recent outbreaks have been reported in peanut crops in Florida and Georgia, our sampling on the west side of the Florida Panhandle resulted in very low larval abundance. This pattern is consistent with a previous study in the western Florida panhandle that documented the first case of BAW resistance to diamides [9] and may reflect the delayed population buildup in this area following annual dispersal from southern overwintering regions.
Our pheromone trap data confirms that moths were present in Santa Rosa County (western Florida panhandle) as early as June. However, the average trap capture per day was substantially lower than that of Jackson Co. (eastern Florida panhandle), which recorded 4.5 times more captures. June temperatures were within the optimal developmental range for BAW [34], with mean daily values of 25.6 °C (21.6–31 °C, min-max respectively), while the reported optimal range for larval development and survival lies between 27–35 °C [34]. This suggests that thermal conditions were suitable for local development, but the relatively reduced adult activity in Santa Rosa County likely constrained local population establishment, contributing to the low larval counts observed in commercial fields. Additionally, BAW populations in the northern Gulf region can overwinter locally during mild winters, despite the absence of a true diapause [6]. However, in areas where persistent overwintering does not occur, local populations typically remain low and depend on annual migration from southern regions to initiate infestations. Historical observations from Louisiana and other southeastern states support this pattern, where isolated fields experienced sporadic infestations from June to August that often coincided with regional outbreaks in neighboring states [35,36]. These records suggest that local overwintering populations, when present, may serve as foci for early-season activity, but widespread outbreaks in the northern Gulf typically rely on migration and favorable seasonal conditions to build damaging populations.
Stable hydrogen isotope analysis revealed four distinct patterns of probable origin, reflecting a mixture of local and long-distance migratory individuals. Although the number of moths used to infer the probability of origin was low, most samples (Patterns 2 and 3, ~73% combined, Figure 4) originated from South Florida and the Caribbean, strongly supporting the hypothesis that the Florida Panhandle acts as a sink for northward migration from overwintering populations in these southern regions [22,23,24,25]. Long-distance movements from northwestern Mexico or the Gulf of California were inferred for a subset of individuals; however, this scenario is unlikely due to multiple geographic barriers, the regional landscape, and prevailing wind patterns. These moths also showed low probability values in the Caribbean, which we consider a more plausible source region for this migratory pattern. Finally, one sample suggested a potential southward (reverse) migration, consistent with the bidirectional seasonal movement observed in other noctuid species such as fall armyworm (S. frugiperda) [23,37,38] and corn earworm (Helicoverpa zea) [22,39,40,41]. These findings highlight that the Florida Panhandle supports a dynamic mix of resident and migratory BAW populations.
The seasonal influx of migratory BAW to the Florida Panhandle has direct implications for both outbreak prediction and insecticide resistance management. First, the timing of larval detections and adult abundance coincides with the mid-season development of peanut and soybean, when crop canopies provide suitable oviposition sites and host quality supports rapid population growth. This seasonal alignment may contribute to the sporadic but damaging outbreaks historically observed in the southeastern USA. Second, the detection of probable origins highlights the risk of resistance allele movement across regions. Previous studies have documented S. frugiperda resistance to chemical insecticides in the southeastern USA [42,43], and BAW resistance in the Florida Panhandle [9,12]. In the southern USA, in addition to peanut and soybean, vegetables such as brassica crops and tomato also serve as hosts for BAW, sustaining populations year-round and acting as sources for infestations in the Florida Panhandle [5]. In addition to chemical insecticides, resistance to the Vip3Aa Bt toxin in cotton has also been reported in North Carolina, increasing selection pressure by Bt traits [44]. Therefore, if moths are moving from high-input regions with high pressure of insecticides, migratory movement could facilitate the spread of these alleles between localities, complicating regional resistance management strategies.
The combination of low local larval abundance, high adult captures, and hydrogen isotope evidence of long-distance dispersal suggests that the Florida Panhandle functions as a migratory hub for BAW. Variation in moth captures between the two counties under study was observed. These counties represent the west and east sides of the Florida Panhandle, and the spatial heterogeneity in adult activity is likely driven by differences in local population buildup and the influence of distinct migratory pathways. These findings provide a foundation for future IPM programs that should couple movement ecology with resistance management, ultimately improving the sustainability of crop protection in the southeastern USA.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/insects16111131/s1. Figure S1: Probability of origin of adults of BAW (samples 1 to 9) collected in the Florida panhandle, FL, USA, based on hydrogen isotope ratios (δ2H). Green color represents higher probability of origin; Figure S2: Probability of origin of adults of BAW (samples 10 to 18) collected in the Florida panhandle, USA, based on hydrogen isotope ratios (δ2H). Green color represents higher probability of origin; Figure S3: Probability of origin of adults of BAW (samples 19 to 26) collected in the Florida panhandle, USA, based on hydrogen isotope ratios (δ2H). Green color represents higher probability of origin; Figure S4: Likely dispersal direction of BAW moths collected in the Florida panhandle, USA; Figure S5: Likely dispersal distance of BAW moths collected in the Florida panhandle, USA; Table S1: Likely dispersal distance and direction based on the posterior probability of origin for each BAW sample collected in the Florida Panhandle, Jay, FL, USA. Data represent the average and percentiles (10th, 50th, and 90th).

Author Contributions

Conceptualization, E.S.C. and S.V.P.-M.; methodology, E.S.C. and S.V.P.-M.; validation, E.S.C., J.G.T.d.M., E.C. and I.L.E.; formal analysis, E.S.C. and J.G.T.d.M.; investigation, E.S.C., J.G.T.d.M., E.C. and I.L.E.; resources, S.V.P.-M.; data curation, E.S.C. and S.V.P.-M.; writing—original draft preparation, E.S.C.; writing—review and editing, J.G.T.d.M., E.C., I.L.E. and S.V.P.-M.; visualization, E.S.C.; supervision, S.V.P.-M.; project administration, S.V.P.-M.; funding acquisition, S.V.P.-M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by USDA Hatch FLA 6203 and Hatch Multistate S1080 n. 6420 (SV Paula-Moraes).

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Materials. Further inquiries can be directed to the corresponding author.

Acknowledgments

We thank the members of the Entomology lab at the West Florida Research and Education Center, UF, for their assistance with insect collection and preparation, and Jason Curtis, from the Department of Geological Sciences, University of Florida, for conducting the hydrogen isotope analysis.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
BAWBeet armyworm
BtBacillus thuringiensis
FAWFall armyworm
IPMIntegrated Pest Management
IRMInsect Resistance Management
SBLSoybean looper
VBCVelvet bean caterpillar
YAWYellow-striped armyworm

References

  1. Capinera, J.L. Handbook of Vegetable Pests; Elsevier: Amsterdam, The Netherlands, 2001; 816p, ISBN 978-0-12-158861-8. [Google Scholar]
  2. Greenberg, S.M.; Sappington, T.W.; Legaspi, B.C.; Liu, T.-X.; Sétamou, M. Feeding and Life History of Spodoptera exigua (Lepidoptera: Noctuidae) on Different Host Plants. Ann. Entomol. Soc. Am. 2001, 94, 566–575. [Google Scholar] [CrossRef]
  3. CABI. Spodoptera exigua (Beet Armyworm). 2019, 29808. Available online: https://www.cabidigitallibrary.org/doi/abs/10.1079/cabicompendium.29808 (accessed on 6 August 2025).
  4. Pearson, A.C. Biology, Population Dynamics, and Pest Status of the Beet Armyworm (Spodoptera exigua) in the Imperial Valley of California. Ph.D. Thesis, University of California, Riverside, CA, USA, 1982. [Google Scholar]
  5. Capinera, J.L. Beet Armyworm, Spodoptera exigua (Hübner) (Insecta: Lepidoptera: Noctuidae); Entomology and Nematology Department, UF/IFAS Extension, University of Florida: Gainesville, FL, USA, 1999. [Google Scholar]
  6. Ruberson, J. Environmental Conditions and Biological Control of the Beet Armyworm. In Proceedings of the Beltwide Cotton Conference, Nashville, TN, USA, 9–12 January 1996; Volume 1, pp. 116–118. [Google Scholar]
  7. Williams, M.R. Cotton Insect Loss Estimates—1998. In Proceedings of the Beltwide Cotton Conference, Orlando, FL, USA, 3–7 January 1999; Volume 2, pp. 807–809. [Google Scholar]
  8. Ruberson, J.; Herzog, G.; Lambert, W.; Lewis, W. Management of the Beet Armyworm: Integration of Control Approaches. In Proceedings of the Beltwide Cotton Conference, San Diego, CA, USA, 5–8 January 1994; National Cotton Council: Memphis, TN, USA, 1994; pp. 857–859. [Google Scholar]
  9. Rabelo, M.M.; Santos, I.B.; Paula-Moraes, S.V. Spodoptera exigua (Hubner) (Lepidoptera: Noctuidae) Fitness and Resistance Stability to Diamide and Pyrethroid Insecticides in the United States. Insects 2022, 13, 365. [Google Scholar] [CrossRef] [PubMed]
  10. Brewer, M.J.; Trumble, J.T. Field Monitoring for Insecticide Resistance in Beet Armyworm (Lepidoptera: Noctuidae). J. Econ. Entomol. 1989, 82, 1520–1526. [Google Scholar] [CrossRef]
  11. Kerns, D.L.; Palumbo, J.C.; Tellez, T. Resistance of Field Strains of Beet Armyworm (Lepidoptera: Noctuidae) from Arizona and California to Carbamate Insecticides. J. Econ. Entomol. 1998, 91, 1038–1043. [Google Scholar] [CrossRef]
  12. Rabelo, M.M.; Paula-Moraes, S.V.; Pereira, E.J.G.; Siegfried, B.D. Contrasting Susceptibility of Lepidopteran Pests to Diamide and Pyrethroid Insecticides in a Region of Overwintering and Migratory Intersection. Pest Manag. Sci. 2020, 76, 4240–4247. [Google Scholar] [CrossRef]
  13. Che, W.; Shi, T.; Wu, Y.; Yang, Y. Insecticide Resistance Status of Field Populations of Spodoptera exigua (Lepidoptera: Noctuidae) from China. J. Econ. Entom. 2013, 106, 1855–1862. [Google Scholar] [CrossRef]
  14. Zuo, Y.; Ma, H.; Lu, W.; Wang, X.; Wu, S.; Nauen, R.; Wu, Y.; Yang, Y. Identification of the Ryanodine Receptor Mutation I4743M and Its Contribution to Diamide Insecticide Resistance in Spodoptera exigua (Lepidoptera: Noctuidae). Insect Sci. 2020, 27, 791–800. [Google Scholar] [CrossRef]
  15. Wang, P.; Yang, F.; Wang, Y.; Zhou, L.-L.; Luo, H.-B.; Zhang, S.; Si, S.-Y. Monitoring the Resistance of the Beet Armyworm (Lepidoptera: Noctuidae) to Four Insecticides in Southern China from 2014 to 2018. J. Econ. Entomol. 2021, 114, 332–338. [Google Scholar] [CrossRef]
  16. Hafeez, M.; Ullah, F.; Khan, M.M.; Li, X.; Zhang, Z.; Shah, S.; Imran, M.; Assiri, M.A.; Fernández-Grandon, G.M.; Desneux, N.; et al. Metabolic-Based Insecticide Resistance Mechanism and Ecofriendly Approaches for Controlling of Beet Armyworm Spodoptera exigua: A Review. Environ. Sci. Pollut. Res. 2022, 29, 1746–1762. [Google Scholar] [CrossRef]
  17. Moraes, J.G.T.; Pereira, E.J.G.; Esquivel, I.L.; Paula-Moraes, S.V. Performance of Chlorantraniliprole against Beet Armyworm Populations from the Florida Panhandle, 2024. Arthropod Manag. Tests 2025, 50, tsaf031. [Google Scholar] [CrossRef]
  18. Mikkola, K.; Salmensuu, P. Migration of Laphygma exigua HB. (Lep., Noctuidae) in Northwestern Europe in 1964. Ann. Zool. Fenn. 1965, 2, 124–139. [Google Scholar]
  19. Wang, X.; Feng, Q.; Zhou, X.; Zhang, H.; Wu, S.; Wu, K. Seasonal Migratory Activity of the Beet Armyworm Spodoptera exigua (Hübner) in the Tropical Area of China. Insects 2024, 15, 986. [Google Scholar] [CrossRef] [PubMed]
  20. Mitchell, E.R. Migration by Spodoptera exigua and S. frugiperda, North American Style. In Movement of Highly Mobile Insects: Concepts and Methodology in Research; North Carolina State University: Raleigh, NC, USA, 1979; pp. 386–393. [Google Scholar]
  21. Hobson, K.A. Tracing Origins and Migration of Wildlife Using Stable Isotopes: A Review. Oecologia 1999, 120, 314–326. [Google Scholar] [CrossRef] [PubMed]
  22. Paula-Moraes, S.V.; Calixto, E.S.; Santos, A.A.; Reay-Jones, F.P.F.; Reisig, D.D.; Farhan, Y.; Smith, J.L.; Hutchison, W.D. Continental-Scale Migration Patterns and Origin of Helicoverpa zea (Lepidoptera: Noctuidae) Based on a Biogeochemical Marker. Environ. Entomol. 2024, 53, nvae034. [Google Scholar] [CrossRef] [PubMed]
  23. Calixto, E.S.; Paula-Moraes, S.V. Hydrogen Stable Isotopes Indicate Reverse Migration of Fall Armyworm in North America. Insects 2025, 16, 471. [Google Scholar] [CrossRef]
  24. Nagoshi, R.N.; Meagher, R.L. Review of Fall Armyworm (Lepidoptera: Noctuidae) Genetic Complexity and Migration. Fla. Entomol. 2008, 91, 546–554. [Google Scholar] [CrossRef]
  25. Tessnow, A.E.; Nagoshi, R.N.; Meagher, R.L.; Fleischer, S.J. Revisiting Fall Armyworm Population Movement in the United States and Canada. Front. Insect Sci. 2023, 3, 1104793. [Google Scholar] [CrossRef]
  26. Brooks, M.E.; Kristensen, K.; van Benthem, K.J.; Magnusson, A.; Berg, C.W.; Nielsen, A.; Skaug, H.J.; Mächler, M.; Bolker, B.M. glmmTMB Balances Speed and Flexibility among Packages for Zero-Inflated Generalized Linear Mixed Modeling. R J. 2017, 9, 378–400. [Google Scholar] [CrossRef]
  27. Fox, J.; Weisberg, S. An R Companion to Applied Regression; Sage Publications: Thousand Oaks, CA, USA, 2019. [Google Scholar]
  28. Lenth, R. Emmeans: Estimated Marginal Means, Aka Least-Squares Means, R package version 1.3.0; R Foundation for Statistical Computing: Vienna, Austria, 2020.
  29. Hobson, K.A.; Wassenaar, L.I. Stable Isotope Ecology: An Introduction. Oecologia 1999, 120, 312–313. [Google Scholar] [CrossRef]
  30. Wassenaar, L.; Hobson, K. Comparative Equilibration and Online Technique for Determination of Non-Exchangeable Hydrogen of Keratins for Use in Animal Migration Studies. Isot. Environ. Health Stud. 2003, 39, 211–217. [Google Scholar] [CrossRef]
  31. Ma, C.; Vander Zanden, H.B.; Wunder, M.B.; Bowen, G.J. assignR: An R Package for Isotope-Based Geographic Assignment. Methods Ecol. Evol. 2020, 11, 996–1001. [Google Scholar] [CrossRef]
  32. R Core Team. R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing: Vienna, Austria, 2024.
  33. Hendricks, D.E.; Hubbard, D.W.; Hardee, D.D. Occurrence of Beet Armyworm Moths in the Lower Mississippi River Delta as Indicated by Numbers Caught in Traps in 1994. Southwest. Entomol. 1995, 20, 157–164. [Google Scholar]
  34. Zhang, H.; Xu, D.; Deng, X.; Liu, Z.; He, Z.; Wu, J.; Zhuo, Z. Impact of Temperature Variation on the Biological Traits and Lifecycle of Spodoptera exigua (Lepidoptera: Noctuidae): A Meta-Analysis Approach. Insects 2025, 16, 155. [Google Scholar] [CrossRef]
  35. Williams, M. Cotton Insect Loss Estimates—1993. In Proceedings of the Beltwide Cotton Conference, San Diego, CA, USA, 5–8 January 1994; pp. 743–763. [Google Scholar]
  36. Burris, E.; Graves, J.B.; Leonard, B.R.; White, C.A. Beet Armyworms (Lepidoptera: Noctuidae) in Northeast Louisiana: Observations on an Uncommon Insect Pest. Fla. Entomol. 1994, 77, 454. [Google Scholar] [CrossRef]
  37. Johnson, S.J. Migration and the Life History Strategy of the Fall Armyworm, Spodoptera frugiperda in the Western Hemisphere. Int. J. Trop. Insect. Sci. 1987, 8, 543–549. [Google Scholar] [CrossRef]
  38. Westbrook, J.; Fleischer, S.; Jairam, S.; Meagher, R.; Nagoshi, R. Multigenerational Migration of Fall Armyworm, a Pest Insect. Ecosphere 2019, 10, e02919. [Google Scholar] [CrossRef]
  39. Gould, F.; Blair, N.; Reid, M.; Rennie, T.; Lopez, J.; Micinski, S. Bacillus Thuringiensis—Toxin Resistance Management: Stable Isotope Assessment of Alternate Host Use by Helicoverpa zea. Proc. Natl. Acad. Sci. USA 2002, 99, 16581–16586. [Google Scholar] [CrossRef]
  40. Westbrook, J.K. Noctuid Migration in Texas within the Nocturnal Aeroecological Boundary Layer. Integr. Comp. Biol. 2008, 48, 99–106. [Google Scholar] [CrossRef]
  41. Westbrook, J.K.; López, J.D. Long-Distance Migration in Helicoverpa zea: What We Know and Need to Know. Southwest. Entomol. 2010, 35, 355–360. [Google Scholar] [CrossRef]
  42. Gutiérrez-Moreno, R.; Mota-Sanchez, D.; Blanco, C.A.; Whalon, M.E.; Terán-Santofimio, H.; Rodriguez-Maciel, J.C.; DiFonzo, C. Field-Evolved Resistance of the Fall Armyworm (Lepidoptera: Noctuidae) to Synthetic Insecticides in Puerto Rico and Mexico. J. Econ. Entomol. 2019, 112, 792–802. [Google Scholar] [CrossRef]
  43. Beuzelin, J.M.; Larsen, D.J.; Roldán, E.L.; Schwan Resende, E. Susceptibility to Chlorantraniliprole in Fall Armyworm (Lepidoptera: Noctuidae) Populations Infesting Sweet Corn in Southern Florida. J. Econ. Entomol. 2022, 115, 224–232. [Google Scholar] [CrossRef]
  44. Reisig, D.; Goldsworthy, E.; Kerns, D.D.; Paula-Moraes, S.V.; Jurat-Fuentes, J.L. First Characterization of Vip3Aa Resistance in Beet Armyworm, Spodoptera exigua (Hübner), Collected from Bollgard 3 Cotton. In Proceedings of the Beltwide Cotton Conferences, New Orleans, LA, USA, 14–16 January 2025. [Google Scholar]
Insects 16 01131 g001
Figure 1. Total number of larvae collected in commercial peanut fields in the FL Panhandle, USA, using the beat cloth method. BAW—Spodoptera exigua, FAW—S. frugiperda, SBL—Chrysodeixis includens, VBC—Anticarsia gemmatalis, YAW—S. ornithogalli.
Figure 1. Total number of larvae collected in commercial peanut fields in the FL Panhandle, USA, using the beat cloth method. BAW—Spodoptera exigua, FAW—S. frugiperda, SBL—Chrysodeixis includens, VBC—Anticarsia gemmatalis, YAW—S. ornithogalli.
Insects 16 01131 g001
Insects 16 01131 g002
Figure 2. Total number of larvae collected in commercial peanut fields in the FL Panhandle, USA, over the crop season using the beat cloth method. BAW—Spodoptera exigua, FAW—S. frugiperda, SBL—Chrysodeixis includens, VBC—Anticarsia gemmatalis, YAW—S. ornithogalli.
Figure 2. Total number of larvae collected in commercial peanut fields in the FL Panhandle, USA, over the crop season using the beat cloth method. BAW—Spodoptera exigua, FAW—S. frugiperda, SBL—Chrysodeixis includens, VBC—Anticarsia gemmatalis, YAW—S. ornithogalli.
Insects 16 01131 g002
Insects 16 01131 g003
Figure 3. Average number of BAW moths per trap per day collected in pheromone traps on the west (Santa Rosa County) and east side (Jackson County) of the Florida Panhandle, USA. Bars represent the mean with standard error. Numbers above each bar represent the average number of moths.
Figure 3. Average number of BAW moths per trap per day collected in pheromone traps on the west (Santa Rosa County) and east side (Jackson County) of the Florida Panhandle, USA. Bars represent the mean with standard error. Numbers above each bar represent the average number of moths.
Insects 16 01131 g003
Insects 16 01131 g004
Figure 4. Probability of origin of BAW collected in the Florida Panhandle region, FL. USA, based on hydrogen isotope ratios (δ2H). Green represents higher probability of origin. Each map represents an example of the dispersal pattern of a single BAW moth specimen. Red dot represents where the moth was collected. Maps of the probability of origin of all samples are in Figures S1–S3.
Figure 4. Probability of origin of BAW collected in the Florida Panhandle region, FL. USA, based on hydrogen isotope ratios (δ2H). Green represents higher probability of origin. Each map represents an example of the dispersal pattern of a single BAW moth specimen. Red dot represents where the moth was collected. Maps of the probability of origin of all samples are in Figures S1–S3.
Insects 16 01131 g004
Insects 16 01131 g005
Figure 5. Four patterns of the likely dispersal direction of BAW moths collected in the Florida Panhandle region, FL, USA. Rose diagrams of the likely dispersal direction and distance of all samples are in Figures S4 and S5.
Figure 5. Four patterns of the likely dispersal direction of BAW moths collected in the Florida Panhandle region, FL, USA. Rose diagrams of the likely dispersal direction and distance of all samples are in Figures S4 and S5.
Insects 16 01131 g005
Table 1. Hydrogen isotope ratio of 26 moths collected during the crop season in the west and east sides of the Florida Panhandle, USA, Santa Rosa and Jackson counties, respectively.
Table 1. Hydrogen isotope ratio of 26 moths collected during the crop season in the west and east sides of the Florida Panhandle, USA, Santa Rosa and Jackson counties, respectively.
Sample IDδ2HDate CollectionFlorida County
1−28.2220 June 2024Santa Rosa
2−21.8520 June 2024Santa Rosa
3−18.1920 June 2024Santa Rosa
4−44.5920 June 2024Santa Rosa
5−46.3222 July 2024Santa Rosa
6−59.1122 July 2024Santa Rosa
7−61.5222 July 2024Santa Rosa
8−63.8422 July 2024Santa Rosa
9−63.9321 August 2024Santa Rosa
10−59.6221 August 2024Santa Rosa
11−63.5621 August 2024Santa Rosa
12−33.4521 August 2024Santa Rosa
13−44.1221 August 2024Santa Rosa
14−40.5610 July 2024Jackson
15−33.3810 July 2024Jackson
16−39.0410 July 2024Jackson
17−44.4110 July 2024Jackson
18−71.027 August 2024Jackson
19−47.527 August 2024Jackson
20−65.977 August 2024Jackson
21−32.707 August 2024Jackson
22−65.417 August 2024Jackson
23−62.4021 August 2024Jackson
24−59.1821 August 2024Jackson
25−60.1721 August 2024Jackson
26−59.8421 August 2024Jackson
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Calixto, E.S.; Moraes, J.G.T.d.; Carter, E.; Esquivel, I.L.; Paula-Moraes, S.V. Dispersal Ecology of the Beet Armyworm in the Florida Panhandle: Implications for Outbreaks and Insecticide Resistance Spread. Insects 2025, 16, 1131. https://doi.org/10.3390/insects16111131

AMA Style

Calixto ES, Moraes JGTd, Carter E, Esquivel IL, Paula-Moraes SV. Dispersal Ecology of the Beet Armyworm in the Florida Panhandle: Implications for Outbreaks and Insecticide Resistance Spread. Insects. 2025; 16(11):1131. https://doi.org/10.3390/insects16111131

Chicago/Turabian Style

Calixto, Eduardo Soares, João Gabriel Tardin de Moraes, Ethan Carter, Isaac L. Esquivel, and Silvana V. Paula-Moraes. 2025. "Dispersal Ecology of the Beet Armyworm in the Florida Panhandle: Implications for Outbreaks and Insecticide Resistance Spread" Insects 16, no. 11: 1131. https://doi.org/10.3390/insects16111131

APA Style

Calixto, E. S., Moraes, J. G. T. d., Carter, E., Esquivel, I. L., & Paula-Moraes, S. V. (2025). Dispersal Ecology of the Beet Armyworm in the Florida Panhandle: Implications for Outbreaks and Insecticide Resistance Spread. Insects, 16(11), 1131. https://doi.org/10.3390/insects16111131

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop