Home Genetic differentiation of three populations of the fall armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae), in Mexico
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Genetic differentiation of three populations of the fall armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae), in Mexico

  • Ana Mabel Martínez-Castillo ORCID logo , Belén Geovana Ayala-Reyes , Jesús Llanderal-Mendoza ORCID logo , Ingrid Lara-De la Cruz , José I. Figueroa-De la Rosa ORCID logo , Yordanys Ramos-González ORCID logo , Samuel Pineda-Guillermo ORCID logo EMAIL logo and Selene Ramos-Ortiz ORCID logo EMAIL logo
Published/Copyright: September 23, 2025
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Florida Entomologist
From the journal Florida Entomologist Volume 108 Issue 1

Abstract

The fall armyworm, Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae), is an important insect pest of maize and numerous other crops throughout the world. In this study, the genetic diversity and structure of three Mexican populations of S. frugiperda, collected from three maize-producing areas in the states of Sinaloa (Sf-SIN), Michoacán (Sf-MICH), and Chiapas (Sf-CHI), were evaluated using the mitochondrial cytochrome oxidase (COI) gene. Neighbor-joining analysis showed that the S. frugiperda sequences of our study were grouped, with 99 % branch support, with reference sequences from Canada, United States of America, and Mexico. Sf-SIN and Sf-CHI sequences were closely related to other Mexican reference sequences, while Sf-MICH sequences formed a well-supported separate clade. AMOVA analysis showed that most of the genetic variability was within populations. The highest correlation between genetic distance and haplotypical frequency was observed between Sf-CHI and Sf-MICH populations. Ten haplotypes were detected considering the three areas sampled and the haplotype diversity was higher in Sf-MICH and Sf-SIN populations. The haplotypic network indicates that two and one individuals from Sf-CHI and Sf-SIN populations, respectively, belonged to the same group. We concluded that the genetic diversity among S. frugiperda populations was more influenced by the variability within individuals of the same population than individuals of different populations. In addition, the presence of shared haplotypes between northwest (Sf-SIN) and southeast (Sf-CHI) individuals possibly indicate a moderate genetic exchange between populations. This diversity is essential for their ability to survive and adapt to environmental changes, which can influence how pest populations respond to control methods.

Resumen

El gusano cogollero, Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae), es una plaga importante del maíz y de numerosos cultivos en el mundo. En este estudio, se evaluó la diversidad genética y la estructura de tres poblaciones mexicanas de S. frugiperda, colectadas en tres zonas productoras de maíz en los estados de Sinaloa (Sf-SIN), Michoacán (Sf-MICH) y Chiapas (Sf-CHI), utilizando el gen citocromo oxidasa mitocondrial (COI). El análisis Neighbor-Joining mostró que las secuencias de S. frugiperda de nuestro estudio se agruparon, con un 99 % de valor de bootstrap, con secuencias de referencia de Canadá, Estados Unidos o México. Las secuencias Sf-SIN y Sf-CHI mostraron mayor relación con otras secuencias de referencia mexicanas, mientras que las secuencias Sf-MICH formaron un clado independiente bien soportado. El análisis AMOVA mostró que la mayor parte de la variabilidad genética fue dentro de las poblaciones. La mayor correlación para la distancia genética y la frecuencia haplotípica se observó entre las poblaciones Sf-CHI y Sf-MICH. Se detectaron diez haplotipos considerando las tres áreas muestreadas; la diversidad de haplotipos fue mayor en las poblaciones Sf-MICH y Sf-SIN. La red haplotípica indicó que tres individuos de la población Sf-SIN y uno de la población Sf-SIN, pertenecieron a un mismo grupo. Concluimos que la presencia de haplotipos compartidos entre individuos del noroeste (Sf-SIN) y del sureste (Sf-CHI) posiblemente indicó un intercambio genético moderado entre poblaciones. Esta diversidad es esencial para su capacidad de sobrevivir y adaptarse a los cambios ambientales, que pueden influir en cómo las poblaciones de plagas responden a los métodos de control.

Keyswords: DNA; PCR; gene flow; haplotype diversity
Palabras clave: ADN; PCR; gen; flujo genético; diversidad haplotípica

1 Introduction

The fall armyworm, Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae), is a highly polyphagous herbivore that can feed on over 350 plant species (Montezano et al. 2018). This insect causes significant economic losses, particularly in maize (Zea mays L.), sorghum (Sorghum bicolor [L.] Moench) (both Poaceae), soybean, (Glycine max [L.] Merr.; Fabaceae), and cotton (Gossypium hirsutum L.; Malvaceae) (Bhavani et al. 2019; Malo and Hore 2020; Overton et al. 2021; Tay et al. 2023). In maize production, yield losses caused by this pest range from 20 to 58 % (Hruska and Gould 1997; Kenis et al. 2023; Kumar et al. 2022) or up to 73 % in certain environmental conditions (Wu et al. 2021).

Spodoptera frugiperda is a species native to tropical and subtropical regions of the Americas, distributed from southern Canada to Argentina (Dew 1913). However, this insect also was reported in West Africa in 2016, followed by its progressive detection across the Old World, where it successfully established on maize and other crops such as wheat, soybean, tomato, and cotton (Goergen et al. 2016; Prasanna et al. 2018; Tay et al. 2022, 2023; Trisyono et al. 2019; Wang et al. 2020). As a result, recent research has explored S. frugiperda ecology, reproductive status, host plant range, insecticide resistance, control methods, and genetic diversity (Gutiérrez-Moreno et al. 2019, 2020; Kenis et al. 2023; Paredes-Sánchez et al. 2021).

A fundamental explanation for S. frugiperda’s broad geographical distribution is its ability to migrate long distances into temperate zones during warmer months to take advantage of seasonal host resources (Nagoshi and Meagher 2022). This migratory behavior has determined important genetic differences between populations and its adaptation to new environments and ecological niches (Kenis et al. 2023; Tay et al. 2022). Various molecular techniques have been employed to study the genetic diversity of S. frugiperda populations, including polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) (Busato et al. 2004; Clark et al. 2007; Lu et al. 1992; McMichael and Prowell 1999; Prowell et al. 2004; Saldamando and Vélez-Arango 2010), simple sequence repeat (SSR) (i.e., microsatellite) loci (Arias et al. 2011; Pavinato et al. 2013), and mitochondrial cytochrome oxidase I (COI) gene haplotypes (Nagoshi et al. 2015; Tay et al. 2022), among others. Knowledge of the structure and genetic diversity of pest populations can help us to understand how insects adapt to environments changes, including variations in host response to insecticides (Booth 2024; Monnerat et al. 2006).

Mitochondrial genes exhibit higher evolutionary rates than nuclear-coded genes (e.g., small subunit ribosomal RNA) and can better discriminate between closely related taxa (Hebert et al. 2003). The COI gene is one of the most conserved mitochondrial protein-coding genes in animals (Mueller 2006). As a barcoding marker, this gene has been used very successfully in many animal taxa, including insects (Folmer et al. 1994; Hebert et al. 2004; Smith et al. 2008; Tay et al. 2022). In addition, this gene is widely used because it only presents maternal inheritance, and therefore, recombination is absent. This allows for establishing an evolutionary history of the taxonomic group to which the organism belongs (Pečnikar and Buzan 2013).

Previous studies have used the COI gene to distinguish between geographically distant S. frugiperda populations, with the potential to delineate the associated migratory pathways (Nagoshi et al. 2012). In this respect, Nagoshi et al. (2015) analyzed populations of this insect from Mexico, Puerto Rico, South America, and the United States. The authors showed that Mexican populations were associated with haplotypes rarely found elsewhere; suggesting limited migratory interactions with foreign populations. In our study, we used the COI gene to assess genetic variability and population structure of fall armyworm collected from three different maize-producing areas of Mexico.

2 Materials and methods

2.1 Insect field collection

Between 30 and 35 third- or fourth-instar S. frugiperda larvae were collected in 2019 from maize in Guasave, Sinaloa (Sf-SIN)and Tapachula, Chiapas (Sf-CHI), Mexico (Table 1, Figure 1). After collection, larvae were individually placed in 28-mL plastic bottles containing 80 % ethanol and then transported to the Instituto de Investigaciones Agropecuarias y Forestales (IIAF), Universidad Michoacana de San Nicolás de Hidalgo (UMSNH), Morelia, Michoacán, Mexico. A third population of S. frugiperda, originally collected in 2019 from maize in Tarímbaro, Michoacán, Mexico (Sf-MICH) and maintained for four generations in the laboratory, also was considered in this study (Table 1). Five voucher specimens of each population were deposited at −80 °C in the insect Collection of Plagas Agrícolas of the IIAF-UMSNH, Tarímbaro, Michoacán, Mexico.

Table 1:

Collection location of Spodoptera frugiperda field populations used in the study.

Collection site (population designation) Collection month Coordinates
IIAF-UMSNH, Michoacán (Sf-MICH) Mar 2019 19.7027778°N, 101.1922222°W
Guasave, Sinaloa (Sf-SIN) May 2019 25.4677778°N, 108.4197222°W
Tapachula, Chiapas (Sf-CHI) Jul 2019 14.9000000°N, 92.2666667°W
Figure 1: Geographic location of Spodoptera frugiperda larvae collected from maize fields in Mexico.
Figure 1:

Geographic location of Spodoptera frugiperda larvae collected from maize fields in Mexico.

2.2 DNA extraction and PCR analysis

Twelve S. frugiperda larvae were used for molecular characterization, three from Sf-CHI, five from Sf-MICH, and four from Sf-SIN. DNA was extracted using the method described by Fitzsimmons et al. (1997). The anterior (head and first thoracic segment) and posterior part (last three abdominal segments) of the body of each larva were cut off and triturated in a lysis buffer (0.6 mL/∼100 mg of tissue): Tris 10 mM pH 7.5–8, ethylenediaminetetraacetic acid 1 mM pH 7.5–8, NaCl (sodium chloride) 10 mM, and sodium dodecyl sulfate 1 %. DNA was purified using the Wizard® Genomic DNA Purification Kit and quantified with a NanoDrop 2000 (Thermo Scientific RMA, Wilmington, Delaware, USA).

A 569-bp fragment of the COI gene was amplified by conventional PCR using the primers FJM767 (5′-GAG​CTG​AAT​TAG​GAC​TCC​AGG-3′) and RJM77R (5′-ATC​ACC​TCC​CCT​GCA​GGA​TC-3′), as described by Levy et al. (2002) for molecular identification of S. frugiperda. The master mix consisted of 10.1 μL ultra-pure water, 5 μL 10× buffer, 1.0 μL dNTPs (deoxynucleoside triphosphates), 0.3 μL FJM76-RJM77 primers, 0.3 μL Taq DNA polymerase, and 3 μL DNA (15 ng). The cycling program included initial denaturation at 94 °C for 3 min, followed by 30 1-min cycles of 94 °C, 50 °C for 1 min of annealing, 72 °C for 1 min; and 72 °C for 3 min for final extension, using a C1000 Touch thermal cycler (Bio-Rad, Foster City, California, USA). Amplified products were visualized by staining with SYBR® Green (Thermo Fisher Scientific Inc., Waltham, Massachusetts) and captured using an Infinity system 3026/WL/LC/26 MX X-Press (Vilber Lourmat, Deutschland GmbH, Ebert).

2.3 DNA sequence analyses

PCR products were purified using ExoSAP (Affymetrix, Santa Clara, California, USA) and sequenced in a 3130 DNA 4-capillary Genetic Analyzer (Applied Biosystems, Foster, California, USA). Sequences were assembled using the BioEdit v.7.0.5 software (Hall 1999) and compared using the Basic Local Alignment Research Tool (BLASTN option) (Altschul et al. 1997) in the National Center for Biotechnology Information (NCBI) platform. This alignment method involved gaps, which are often inserted during the alignment of homologous regions of sequences and represent deletions or insertions (indels) (Higgins et al. 2005). Sequences were compared with nine S. frugiperda sequences retrieved from GenBank, including sequences from Canada (GU439151.1), United States of America (HM136586.1, GU439151.1, and LC508876.1, HM102314.1), and Mexico (KF872171.1, KF872172.1, MN833796.1, KF872173.1). These sequences were chosen based on geographic origin, which allowed us to establish phylogenetic relationships among Mexican S. frugiperda populations and those from other regions of North America. All selected sequences were validated for quality and completeness before inclusion in the analysis.

A neighbor-joining (NJ) similarity analysis (Saitou and Neim 1987) was used to determine the genetic similarity among the sequences of S. frugiperda. Sequences of Helicoverpa zea (Boddie) (Lepidoptera: Noctuidae) (JF855191), S. ornithogalli (Guenée) (JF855012.1), S. litura (Fabricius) (HQ991355.1), and S. exigua (Hübner) (MK318332.1), also downloaded from GenBank, were used as outgroups. A bootstrap consensus tree (1,000 replicates) was constructed to infer the evolutionary history of the analyzed taxa (Felsenstein 1985). Branches with support values below 50 % were collapsed, and bootstrap support values were displayed next to the corresponding branches. The percentage of replicate trees where the associated taxa clustered together in the bootstrap test is shown next to the branches. Molecular distances were computed using the maximum composite likelihood method (Tamura et al. 2004). There were a total of 653 positions in the final dataset. Molecular analyses were conducted in MEGA 11 software (Stecher et al. 2020; Tamura et al. 2004).

2.4 Genetic differentiation

An analysis of molecular variation (AMOVA) was performed to assess the genetic variability among and within populations using Arlequin software version 3.1 (Excoffier et al. 2005). Nucleotide polymorphisms were analyzed with the DNA Sequence Polymorphism program (DNASP version 6.12.03x64), which estimated the variation of DNA sequences within and between the three Mexican S. frugiperda populations (for non-coding regions, synonymous or non-synonymous sites or in various types of codon positions), as well as the linkage imbalance, recombination, gene flow and gene conversion parameters (Librado and Rozas 2009). A TCS (Templeton-Crandall-Sing) program was used to construct haplotype networks (Metro et al. 2000). This program also was used to analyze the genetic distance between pairs of S. frugiperda populations used in this study.

3 Results

3.1 COI gene sequences and neighbor-joining similarity analysis

A total of 12 sequences were obtained from the three S. frugiperda populations: five from Sf-MICH, three from Sf-CHI, and four from Sf-SIN.

The tree topology, with H. zea as an outgroup, demonstrated several well-supported clades with bootstrap values ranging from 91 to 99 % (Figure 2). The upper clade comprised S. frugiperda individuals from Canada (GU439151.1) and the United States of America (LC508876.1 and HM102314.1), showing a close genetic affinity with specimens from Florida (HM136586.1). This group was followed by a distinct cluster of Mexican reference individuals from various states, including Sinaloa, Tamaulipas, Coahuila, and Chiapas (KF872171.1, KF872172.1, MN833796.1, KF872173.1, respectively). Three Sf-CHI (Sf-CHI 01, Sf-CHI 02, and Sf-CHI 03) and four Sf-SIN (Sf-SIN 01, Sf-SIN 02, Sf-SIN 03, and Sf-SIN 04) sequences were genetically related to Mexican reference sequences, while five Sf-MICH (Sf-MICH 01, Sf-MICH 02, Sf-MICH 03, Sf-MICH 04, and Sf-MICH 05) sequences formed a well-supported and separated clade. One S. frugiperda sequence from Tabasco (ON038434.1) was observed as a single external sequence. The other Spodoptera species (S. ornithogalli, S. litura, and S. exigua) appeared in basal positions in the phylogeny.

Figure 2: The phylogenetic tree inferred using the neighbor-joining (NJ) method from COI sequences of Spodoptera frugiperda. Twelve sequences were obtained from larvae collected in maize crops across the states of Michoacán (Sf-MICH), Sinaloa (Sf-SIN), and Chiapas (Sf-CHI). These sequences were compared with 13 noctuid species sequences retrieved from GenBank, including S. frugiperda samples from the United States, Canada, and Mexico (Sinaloa, Tamaulipas, Coahuila, Chiapas, and Tabasco), as well as additional external sequences: Helicoverpa zea, Spodoptera ornithogalli, S. litura, and S. exigua. The tree was resampled with 1,000 bootstrap replicates, and branch lengths are presented as the number of base substitutions per site.
Figure 2:

The phylogenetic tree inferred using the neighbor-joining (NJ) method from COI sequences of Spodoptera frugiperda. Twelve sequences were obtained from larvae collected in maize crops across the states of Michoacán (Sf-MICH), Sinaloa (Sf-SIN), and Chiapas (Sf-CHI). These sequences were compared with 13 noctuid species sequences retrieved from GenBank, including S. frugiperda samples from the United States, Canada, and Mexico (Sinaloa, Tamaulipas, Coahuila, Chiapas, and Tabasco), as well as additional external sequences: Helicoverpa zea, Spodoptera ornithogalli, S. litura, and S. exigua. The tree was resampled with 1,000 bootstrap replicates, and branch lengths are presented as the number of base substitutions per site.

3.2 Genetic differentiation and haplotypic grouping

AMOVA results revealed that 56.5 % of the genetic variability was within the same Mexican population analyzed (F ST = 0.44496; P < 0.05, Table 2). The highest correlation between genetic distance (i.e., population differentiation due to genetic structure) and haplotypical frequency was observed between Sf-CHI and Sf-MICH populations, followed by Sf-MICH and Sf-Sinaloa and Sf-CHI and Sf-SIN (Table 3).

Table 2:

Molecular analysis of variance (AMOVA) for Spodoptera frugiperda populations collected in the states of Chiapas, Michoacán, and Sinaloa, Mexico.

Source of variation df Sum of squares Variance components Percentage of variation
Among populations 2 11.270 1.09310 Va 43.50
Within populations 9 12.310 1.37590 Vb 56.50
Total 11 23.580 2.46900 100.0
Fixation indice * F ST = 0.44496

  1. Va, variance of component a; Vb, variance of component b.

Table 3:

Genetic distance between pairs of Spodoptera frugiperda populations collected in the states of Chiapas (Sf-CHI), Michoacán (Sf-MICH), and Sinaloa (Sf-SIN), Mexico.

Population 1 Population 2 Coefficient of genetic differentiation Genetic differentiation (haplotypical frequency) Fixing rate
Sf-CHI Sf-MICH 0.11765 0.61339 0.61184
Sf-CHI Sf-SIN 0.00297 0.11509 0.11429
Sf-MICH Sf-SIN 0.02679 0.46143 0.01240

Ten haplotypes were detected considering the three S. frugiperda populations collected (Table 2). The numbers of segregating sites, haplotypes, haplotype diversity, and nucleotide diversity were higher in Sf-MICH and Sf-SIN populations than in the Sf-CHI population (Table 4). The Sf-MICH and Sf-SIN populations were associated with four haplotypes, while the Sf-CHI population was associated with two haplotypes (Table 4). The haplotypic grouping indicated a well-resolved network (Figure 3): a main group contained three sequences from Sf-CHI and a sequence from Sf-SIN. From this group, three haplotypic subgroups are derived: i) four sequences from Sf-MICH, ii) three sequences from Sf-SIN, and iii) an individual sequence from Sf-CHI.

Table 4:

Genetic variability analysis of COI gene of Spodoptera frugiperda populations collected in the states of Chiapas (Sf-CHI), Michoacán (Sf-MICH), and Sinaloa (Sf-SIN), Mexico.

Populations Number of sequences Segregating sites Haplotypes Haplotype diversity Nucleotide diversity
Sf-CHI 3 2 2 0.667 0.00278
Sf-MICH 5 5 4 0.900 0.00542
Sf-SIN 4 7 4 1.000 0.00799
Total data 12 13 10 0.939 PiT: 0.00893
Figure 3: COI gene haplotypes of Spodoptera frugiperda from three populations collected in maize crops from the states of Chiapas (Sf-CHI), Michoacán (Sf-MICH), and Sinaloa (Sf-SIN), Mexico. In green, the ancestral group; in gray individuals of Sf-SIN; in blue individuals of Sf-MICH and red individuals of Sf-CHI. The size of the box represents the number of nested haplotypes.
Figure 3:

COI gene haplotypes of Spodoptera frugiperda from three populations collected in maize crops from the states of Chiapas (Sf-CHI), Michoacán (Sf-MICH), and Sinaloa (Sf-SIN), Mexico. In green, the ancestral group; in gray individuals of Sf-SIN; in blue individuals of Sf-MICH and red individuals of Sf-CHI. The size of the box represents the number of nested haplotypes.

4 Discussion

The migratory behavior of S. frugiperda has determined important genetic differences between populations with adaptations to new environments (Kenis et al. 2023; Tay et al. 2022). For this reason, an important number of studies have been conducted to compare the genetic variation of this insect over large geographical areas in the Americas (Busato et al. 2004; McMichael and Prowell 1999; Nagoshi et al. 2012, 2015; Pashley et al. 1985; Pecina-Quintero et al. 2015; Salinas-Hernández and Saldamando-Benjumea 2011) as well as of recent invasive populations in Africa, China, and India (Nagoshi et al. 2022; Tay et al. 2022). Our study was focused on determining the genetic association among three Mexican S. frugiperda populations collected in three maize-producing areas and their genetic structure and haplotype frequency using the COI gene.

Based on the neighbor-joining similarity analysis (91–99 %), our results showed a clear organization of Mexican populations into distinctive clades. The Mexican reference sequences (Sinaloa, Tamaulipas, Coahuila, and Chiapas) formed a monophyletic group, distinct from the North American populations (Canada and United States of America), which show a close phylogenetic relationship. This grouping may be explained by insect migration and/or the intense commercial exchange of maize between these important producing regions, facilitating gene flow through the anthropogenic movement of germplasm (Cano-Calle et al. 2015; De Souza et al. 2015). This might also explain the genetic similarity of the two most distant Mexican populations of S. frugiperda in our study (Sf-CHI and Sf-SIN).

In contrast, the S. frugiperda population from Michoacán (Sf-MICH) formed a well-defined and separate clade, suggesting possible genetic isolation (Belay et al. 2012; Dumas et al. 2015; Hu et al. 2023). This could be attributed to the presence of geographic barriers, such as mountains and valleys, in this state, which may limit gene flow with other populations of this insect (Hu et al. 2023). In addition, the abundance of native maize in this state (Orozco-Ramírez et al. 2017), and their local commercialization, could reduce the possibility of genetic exchange (Clark et al. 2007). Similarly, the reference population from Tabasco appeared as an independent lineage, also suggesting the presence of geographic barriers and/or that this population could be subject to particular environmental conditions (Arias et al. 2019; Nagoshi et al. 2015).

Similar to that observed in the neighbor-joining similarity analysis, most of the genetic variability was observed within individuals of the same populations (56.5 %) than among populations (43.5 %), which is similar to results obtained by De Souza et al. (2015), who observed high variability within six S. frugiperda populations from maize fields in Brazil using simple sequence repeat (SSR) markers. In this regard, these authors reported that local populations are the principal reservoir of genetic variability. In general, the abundance of genetic differentiation within populations is generally considered the result of insufficient gene flow coupled with selective pressures. In addition, this low dispersion among populations may facilitate local adaptation (Chen et al. 2015; Hülber et al. 2015; Slatkin 1987). Similarly, in an amplified fragment length polymorphism (AFLP) analysis with 23 S. frugiperda populations collected in maize crops in the Americas, 11 of them from Mexico, showed that most of the genetic variability was within populations and that gene flow across these populations was low (Clark et al. 2007). This same pattern also has been reported in nine S. frugiperda populations collected from four geographical areas in Colombia using AFLP (Lobo-Hernández and Saldamando-Benjumea 2012). In contrast, high gene flow was reported across 11 or 12 Colombian (Salinas-Hernández and Saldamando-Benjumea 2011) and Brazilian (Ishizuka et al. 2023) populations from five and nine geographical areas, respectively, using the COI gene and a genotyping-by-sequencing (GBS) approach, respectively.

In our study, the F ST value (0.44495) indicated the significant existence of high population structuring among the three S. frugiperda populations analyzed (Hartl and Clarck 1997). Genetic distance analysis showed that all sequences from the Sf-MICH population had greater genetic distance compared with the Sf-CHI population, indicating low gene flow between these populations. In contrast, the genetic distance values of Sf-CHI versus Sf-SIN and Sf-MICH versus Sf-SIN populations were low (≤0.02679). Similarly, Brazilian populations of S. frugiperda had very low F ST values (<0.006, Ishizuka et al. 2023), suggesting a high gene flow among locations.

In agreement with our study, genetic variability also has been reported in populations collected exclusively from maize crops. For example, Nagoshi et al. (2015) found that haplotypes from three Mexican populations collected were mostly associated with local populations, suggesting limited migration from other populations in the Western Hemisphere. Similarly, a gene diversity analysis of AFLP with several S. frugiperda populations collected from maize plants in the Western Hemisphere showed a low level of gene migration into a given population, with less viability between populations than within (Clark et al. 2007). De Souza et al. (2015) determined a moderate genetic differentiation among the S. frugiperda populations collected from maize in Brazil, which may be a consequence of an increase in isolation between geographically distant localities. Similarly, Nagoshi et al. (2015) determined that five Mexican S. frugiperda populations, three from laboratory colonies derived from widely separated populations in Mexico (Durango, Sinaloa, Tamaulipas, and Chiapas) and two from specimens that were obtained from maize fields in Durango and Tamaulipas, were associated with haplotypes rarely found elsewhere, suggesting limited migratory interaction with foreign populations.

Our haplotype network showed the formation of a main group containing sequences from Sf-CHI and Sf-SIN populations, which may suggest the introduction of a maternal lineage whose progeny may have dispersed from north to south. In addition, four haplotypes identified in the Sf-MICH population formed a subgroup that has remained with minimal genetic changes, coinciding with the highest genetic distance with the Sf-CHI population.

In general, the genetic structure among S. frugiperda populations in Mexico could have significant implications for its management as different populations could develop specific local adaptations, including variations in response to insecticides (Booth 2024; Pélissié et al. 2018). In this regard, different levels of susceptibility of different S. frugiperda populations from Mexico to conventional and biorational insecticides, including Bacillus thuringiensis Berliner (Caryophanales: Bacilliaceae) cry toxins, were possibly due to natural genetic variation and/or insect migration within the different agricultural regions sampled (Gutiérrez-Moreno et al. 2019, 2020; Monnerat et al. 2006).

We conclude that the genetic diversity among S. frugiperda populations studied here was more influenced by the variability within individuals of the same population than individuals of different populations, likely reflecting a moderate genetic exchange. However, one of the populations (Sf-MICH) analyzed showed a possible genetic isolation. These results call for further studies to determine the genetic variability in S. frugiperda populations and to analyze a large sample, including individuals from other Mexican regions.

Corresponding authors: Samuel Pineda-Guillermo, Instituto de Investigaciones Agropecuarias y Forestales, Universidad Michoacana de San Nicolás de Hidalgo, Tarímbaro, Michoacán, Mexico, E-mail: ; and Selene Ramos-Ortiz, Secretaria de Ciencia, Humanidades, Tecnología e Innovación (SECIHTI)-Instituto de Investigaciones Agropecuarias y Forestales, Universidad Michoacana de San Nicolás de Hidalgo, Tarímbaro, Michoacán, Mexico, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: Conceptualization, investigation, data analysis, writing – original draft, writing – review and editing, A.M.M-C.; methodology, writing – review and editing, B.G. A-R.; data analysis and writing – review and editing, J. L-M.; methodology, writing – review and editing, I. L-D.; review and editing, J. I. F-D.; review and editing, Y.R-G.; conceptualization, writing – review and editing, S.P-G.; data analysis, supervision, writing – review and editing, S.R-O. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The author states no conflict of interest.

  6. Research funding: This work was supported by the Coordinación de la Investigación Científica, Universidad Michoacana de San Nicolás de Hidalgo, and the Instituto de Ciencia, Tecnología e Innovación (Projects FCCHTI23_ME-4.1.-0070 to S.R.O. and FCCHTI23_ME-4.1.-0064 to A.M.M.C).

  7. Data availability: Data available from the corresponding author upon request.

References

Altschul, S.F., Madden, T.L., Schäffer, A.A., Zhang, J., Zhang, Z., Miller, W., and Lipman, D.J. (1997). Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25: 3389–3402, https://doi.org/10.1093/nar/25.17.3389.Search in Google Scholar PubMed PubMed Central

Arias, R.S., Blanco, C.A., Portilla, M., Snodgrass, G.L., and Scheffler, B.E. (2011). First microsatellites from Spodoptera frugiperda (Lepidoptera: Noctuidae) and their potential use for population genetics. Ann. Entomol. Soc. Am. 104: 576–587, https://doi.org/10.1603/an10135.Search in Google Scholar

Arias, O., Cordeiro, E., Corrêa, A.S., Domingues, F.A., Guidolin, A.S., and Omoto, C. (2019). Population genetic structure and demographic history of Spodoptera frugiperda (Lepidoptera: Noctuidae): implications for insect resistance management programs. Pest Manage. Sci. 75: 2948–2957, https://doi.org/10.1002/ps.5407.Search in Google Scholar PubMed

Belay, D.K., Clark, P.L., Skoda, S.R., Isenhour, D.J., Molina-Ochoa, J., Gianni, C., and Foster, J.E. (2012). Spatial genetic variation among Spodoptera frugiperda (Lepidoptera: Noctuidae) sampled from the United States, Puerto Rico, Panama, and Argentina. Ann. Entomol. Soc. Am. 105: 359–367, https://doi.org/10.1603/an11111.Search in Google Scholar

Bhavani, B., Chandra, S.V., Kishore Varma, P., Bharatha Lakshmi, M., Jamuna, P., and Swapna, B. (2019). Morphological and molecular identification of an invasive insect pest, fall armyworm, Spodoptera frugiperda, occurring on sugarcane in Andhra Pradesh, India. J. Entomol. Zool. Stud. 7: 12–18.Search in Google Scholar

Booth, W. (2024). Population genetics as a tool to understand invasion dynamics and insecticide resistance in indoor urban pest insects. Cur. Opin. Insect Sci. 62: 101166, https://doi.org/10.1016/j.cois.2024.101166.Search in Google Scholar PubMed

Busato, G.R., Grützmacher, A.D., Oliveira, A.C.D., Vieira, E.A., Zimmer, P.D., Kopp, M.M., and Magalhães, T.R. (2004). Análise da estrutura e diversidade molecular de populações de Spodoptera frugiperda (JE Smith) (Lepidoptera: Noctuidae) associadas às culturas de milho e arroz no Rio Grande do Sul. Neotrop. Entomol. 33: 709–716.10.1590/S1519-566X2004000600008Search in Google Scholar

Cano-Calle, D., Arango-Isaza, R.E., and Saldamando-Benjumea, C.I. (2015). Molecular identification of Spodoptera frugiperda (Lepidoptera: Noctuidae) corn and rice strains in Colombia by using a PCR-RFLP of the mitochondrial gene cytochrome oxydase I (COI) and a PCR of the gene FR (for rice). Ann. Entomol. Soc. Am. 108: 172–180, https://doi.org/10.1093/aesa/sav001.Search in Google Scholar

Chen, H., He, R., Wang, Z.L., Wang, S.Y., Chen, Y., Zhu, Z.C., and Chen, X.M. (2015). Genetic diversity and variability in populations of the white wax insect Ericerus pela, assessed by AFLP analysis. Genet. Mol. Res. 14: 17820–17827, https://doi.org/10.4238/2015.december.22.6.Search in Google Scholar

Clark, P.L., Molina-Ochoa, J., Martinelli, S., Skoda, S.R., Isenhour, D.J., Lee, D.J., Krumm, J.T., and Foster, J.E. (2007). Population variation of the fall armyworm, Spodoptera frugiperda, in the Western Hemisphere. J. Insect Sci. 7: 5–10, https://doi.org/10.1673/031.007.0501.Search in Google Scholar PubMed PubMed Central

De Souza, I.R.P., Mendes, S.M., Rafael, H.A., De Almedia Barrros, B., Pinto, M.D.O., Carneiro, N.P., Lana, U.G.D.P., Landau, E.C., Gomes, C.A., and Pastina, M.M. (2015). Population structure of Spodoptera frugiperda collected in maize from different Brazilian geographic regions. Rev. Bras. Milho Sorgo 14: 300–315, https://doi.org/10.18512/1980-6477/rbms.v14n3p300-315.Search in Google Scholar

Dew, J.A. (1913). Fall army worm. J. Econ. Entomol. 6: 361–366, https://doi.org/10.1093/jee/6.4.361.Search in Google Scholar

Dumas, P., Dumas, P., Legeai, F., Lemaitre, C., Scaon, E., Orsucci, M., Orsucci, M., Labadie, K., Gimenez, S., Clamens, A.-L, et al.. (2015). Spodoptera frugiperda (Lepidoptera: Noctuidae) host-plant variants: two host strains or two distinct species? Genetica 143: 305–316, https://doi.org/10.1007/s10709-015-9829-2.Search in Google Scholar PubMed PubMed Central

Excoffier, L., Laval, G., and Schneider, S. (2005). Arlequin (ver 3.0): an integrated software package for population genetics data analysis. Evol. Bioinform. Online 1: 47–50.10.1177/117693430500100003Search in Google Scholar

Felsenstein, J. (1985). Confidence limits on phylogenies: an approach using the bootstrap. Evolution 39: 783–791, https://doi.org/10.1111/j.1558-5646.1985.tb00420.x.Search in Google Scholar PubMed

Fitzsimmons, N.N., Moritz, C., Limpus, C.J., Pope, L., and Prince, R. (1997). Geographic structure of mitochondrial and nuclear gene polymorphisms in Australian green turtle populations and male-biased gene flow. Genetics 147: 1843–1854, https://doi.org/10.1093/genetics/147.4.1843.Search in Google Scholar PubMed PubMed Central

Folmer, R.H.A., Nilges, M., Folkers, P.J.M., Konings, R.N.H., and Hilbers, C.W. (1994). A model of the complex between single-stranded DNA and the single-stranded DNA binding protein encoded by gene V of filamentous bacteriophage M13. J. Mol. Biol. 240: 341–357, https://doi.org/10.1006/jmbi.1994.1449.Search in Google Scholar PubMed

Goergen, G., Kumar, P.L., Sankung, S.B., Togola, A., and Tamò, M. (2016). First report of outbreaks of the fall armyworm Spodoptera frugiperda (JE Smith) (Lepidoptera, Noctuidae). A new alien invasive pest in West and Central Africa. PLoS One 11: e0165632, https://doi.org/10.1371/journal.pone.0165632.Search in Google Scholar PubMed PubMed Central

Gutiérrez-Moreno, R., Mota-Sanchez, D., Blanco, C.A., Chandrasena, D., Difonzo, C., Conner, J., Head, G., Berman, K., and Wise, J. (2020). Susceptibility of fall armyworms (Spodoptera frugiperda JE) from Mexico and Puerto Rico to Bt proteins. Insects 11: 831, https://doi.org/10.3390/insects11120831.Search in Google Scholar PubMed PubMed Central

Gutiérrez-Moreno, R., Mota-Sanchez, D., Blanco, C.A., Whalon, M.E., Terán-Santofimio, H., Rodriguez-Maciel, J.C., and DiFonzo, C. (2019). Field-evolved resistance of the fall armyworm (Lepidoptera: Noctuidae) to synthetic insecticides in Puerto Rico and Mexico. J. Econ. Entomol. 112: 92802.10.1093/jee/toy372Search in Google Scholar PubMed

Hall, T.A. (1999). BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp. Ser. 41: 95–98.Search in Google Scholar

Hartl, D.L. and Clarck, A.G. (Eds.) (1997). Principles of population genetics, 3rd ed. Massachusetts, United States of America: Sinauer Associates Inc.Search in Google Scholar

Hebert, P.D.N., Cywinska, A., Ball, S.L., and Dewaard, J.R. (2003). Biological identifications DNA barcodes. Phil. Trans. Roy. Soc. Lond. B 270: 313–321, https://doi.org/10.1098/rspb.2002.2218.Search in Google Scholar PubMed PubMed Central

Hebert, P.D.N., Penton, E.H., Burns, J.M., Janzen, D.H., and Hallwachs, W. (2004). Ten species in one: DNA barcoding reveals cryptic species in the neotropical skipper butterfly Astraptes fulgerator. Proc. Natl. Acad. Sci. USA 101: 12–17, https://doi.org/10.1073/pnas.0406166101.Search in Google Scholar PubMed PubMed Central

Higgins, J.D., Sanchez-Moran, E., Armstrong, S.J., Jones, G.H., and Franklin, F.C.H. (2005). The Arabidopsis synaptonemal complex protein ZYP1 is required for chromosome synapsis and normal fidelity of crossing over. Genes Dev. 19: 2488–2500, https://doi.org/10.1101/gad.354705.Search in Google Scholar PubMed PubMed Central

Hruska, A.J. and Gould, F. (1997). Fall armyworm (Lepidoptera: Noctuidae) and Diatraea lineolata (Lepidoptera: Pyralidae): impact of larval population level and temporal occurrence on maize yield in Nicaragua. J. Econ. Entomol. 90: 611–622, https://doi.org/10.1093/jee/90.2.611.Search in Google Scholar

Hu, Z., Yang, F., Zhang, D., Zhang, S., Yu, X.-F., and Yang, M.-F. (2023). Genetic diversity and fine-scale genetic structure of Spodoptera litura Fabricius (Lepidoptera: Noctuidae) in Southern China based on microsatellite markers. Animals 13: 560.10.3390/ani13040560Search in Google Scholar PubMed PubMed Central

Hülber, K., Sonnleitner, M., Suda, J., Krejčíková, J., Schönswetter, P., Schneeweiss, G.M., and Winkler, M. (2015). Ecological differentiation, lack of hybrids involving diploids, and asymmetric gene flow between polyploids in narrow contact zones of Senecio carniolicus (syn. Jacobaea carniolica, Asteraceae). Ecol. Evol. 5: 1224–1234, https://doi.org/10.1002/ece3.1430.Search in Google Scholar PubMed PubMed Central

Ishizuka, T.K., Cordeiro, E.M.G., Alves-Pereira, A., de Araújo Batista, C.E., Murúa, M.G., Pinheiro, J.B., Sethi, A., Nagoshi, R.N., Foresti, J., and Zucchi, M.I. (2023). Population genomics of fall armyworm by genotyping-by-sequencing: implications for pest management. PLoS One 18: e0284587, https://doi.org/10.1371/journal.pone.0284587.Search in Google Scholar PubMed PubMed Central

Kenis, M., Benelli, G., Biondi, A., Calatayud, P.A., Day, R., Desneux, N., Harrison, R.D., Kriticos, D., Rwomushana, I., van den Berg, J, et al.. (2023). Invasiveness, biology, ecology, and management of the fall armyworm, Spodoptera frugiperda. Entomol. Gen. 43: 187–241, https://doi.org/10.1127/entomologia/2022/1659.Search in Google Scholar

Kumar, R.M., Gadratagi, B.G., Paramesh, V., Kumar, P., Madivalar, Y., Narayanappa, N., and Ullah, F. (2022). Sustainable management of invasive fall armyworm, Spodoptera frugiperda. Agronomy 12: 2150, https://doi.org/10.3390/agronomy12092150.Search in Google Scholar

Levy, C.H., Garcia-Maruniak, A., and Maruniak, J. (2002). Strain identification of Spodoptera frugiperda (Lepidoptera: Noctuidae) insects and cell line: PCR-RFLP of cytochrome oxidase c subunit I gene. Fla. Entomol. 85: 186–190, https://doi.org/10.1653/0015-4040(2002)085[0186:siosfl]2.0.co;2.10.1653/0015-4040(2002)085[0186:SIOSFL]2.0.CO;2Search in Google Scholar

Librado, P. and Rozas, J. (2009). DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25: 1451–1452, https://doi.org/10.1093/bioinformatics/btp187.Search in Google Scholar

Lobo-Hernández, M.I. and Saldamando-Benjumea, C.I. (2012). Molecular characterization and genetic differentiation of Spodoptera frugiperda JE Smith (Lepidoptera: Noctuidae) in maize, rice, and cotton fields of Colombia with AFLP. Southwest. Entomol. 37: 193–207, https://doi.org/10.3958/059.037.0213.Search in Google Scholar

Lu, Y.J., Adang, M.J., Isenhour, D.J., and Kochert, G.D. (1992). RFLP analysis of genetic variation in North American populations of the fall armyworm moth Spodoptera frugiperda (Lepidoptera: Noctuidae). Mol. Ecol. 1: 199–208, https://doi.org/10.1111/j.1365-294x.1992.tb00178.x.Search in Google Scholar

Malo, M. and Hore, J. (2020). The emerging menace of fall armyworm (Spodoptera frugiperda JE Smith) in maize: a call for attention and action. J. Entomol. Zool. Stud. 8: 455–465.Search in Google Scholar

McMichael, M. and Prowell, D.P. (1999). Differences in amplified fragment length polymorphism in fall armyworm (Lepidoptera: Noctuidae) host strains. Ann. Entomol. Soc. Am. 92: 175–181, https://doi.org/10.1093/aesa/92.2.175.Search in Google Scholar

Metro, C., Posada, D., and Crandall, K.A. (2000). TCS: a computer program to estimate gene genealogies. Mol. Ecol. 9: 1657–1659, https://doi.org/10.1046/j.1365-294x.2000.01020.x.Search in Google Scholar PubMed

Monnerat, R., Martins, E., Queiroz, P., Ordúz, S., Jaramillo, G., Benintende, G., Cozzi, J., Real, M.D., Martinez-Ramirez, A., Rausell, C., et al. (2006). Genetic variability of Spodoptera frugiperda Smith (Lepidoptera: Noctuidae) populations from Latin America is associated with variations in susceptibility to Bacillus thuringiensis Cry toxins. Appl. Environ. Microbiol. 72: 7029–7035, https://doi.org/10.1128/aem.01454-06.Search in Google Scholar

Montezano, D.G., Specht, A., Sosa-Gómez, D.R., Roque-Specht, V.F., Sousa-Silva, J.C., Paula-Moraes, S.D., Peterson, J.A., and Hunt, T.E. (2018). Host plants of Spodoptera frugiperda (Lepidoptera: Noctuidae) in the Americas. Afr. Entomol. 26: 286–300, https://doi.org/10.4001/003.026.0286.Search in Google Scholar

Mueller, R.L. (2006). Evolutionary rates, divergence dates, and the performance of mitochondrial genes in Bayesian phylogenetic analysis. Syst. Biol. 55: 289–300, https://doi.org/10.1080/10635150500541672.Search in Google Scholar PubMed

Nagoshi, R.N. and Meagher, R.L. (2022). The Spodoptera frugiperda host strains: what they are and why they matter for understanding and controlling this global agricultural pest. J. Econ. Entomol. 115: 1729–1743, https://doi.org/10.1093/jee/toac050.Search in Google Scholar PubMed

Nagoshi, R.N., Goergen, G., Koffi, D., Agboka, K., Adjevi, A.K.M., Du Plessis, H., Van de Berg, J., Tepa-Yotto, G.T., Winsou, J.K., Meagher, R.L, et al.. (2022). Genetic studies of fall armyworm indicate a new introduction into Africa and identify limits to its migratory behavior. Sci. Rep. 12: 1941, https://doi.org/10.1038/s41598-022-05781-z.Search in Google Scholar PubMed PubMed Central

Nagoshi, R.N., Meagher, R.L., and Hay-Roe, M. (2012). Inferring the annual migration patterns of fall armyworm (Lepidoptera: Noctuidae) in the United States from mitochondrial haplotypes. Ecol. Evol. 2: 1458–1467, https://doi.org/10.1002/ece3.268.Search in Google Scholar PubMed PubMed Central

Nagoshi, R.N., Rosas-García, N.M., Meagher, R.L., Fleischer, S.J., Westbrook, J.K., Sappington, T.W., Hay-Roe, M., Thomas, J.M.G., and Murúa, G.M. (2015). Haplotype profile comparisons between Spodoptera frugiperda (Lepidoptera: Noctuidae) populations from Mexico with those from Puerto Rico, South America, and the United States and their implications to migratory behavior. J. Econ. Entomol. 108: 135–144, https://doi.org/10.1093/jee/tou044.Search in Google Scholar PubMed

Orozco-Ramírez, Q., Perales, H., and Hijmans, R.J. (2017). Geographical distribution and diversity of maize (Zea mays L. subsp. mays) races in Mexico. Genet. Resour. Crop Evol. 64: 855–865, https://doi.org/10.1007/s10722-016-0405-0.Search in Google Scholar

Overton, K., Maino, J.L., Day, R., Umina, P.A., Bett, B., Carnovale, D., Ekesi, S., Meagher, R., and Reynolds, O.L. (2021). Global crop impacts, yield losses, and action thresholds for fall armyworm (Spodoptera frugiperda): a review. Crop Prot. 145: 105641, https://doi.org/10.1016/j.cropro.2021.105641.Search in Google Scholar

Paredes-Sánchez, F.A., Rivera, G., Bocanegra-García, V., Martínez-Padrón, H.Y., Berrones Morales, M., Niño-García, N., and Herrera-Mayorga, V. (2021). Advances in control strategies against Spodoptera frugiperda. A review. Molecules 26: 5587, https://doi.org/10.3390/molecules26185587.Search in Google Scholar PubMed PubMed Central

Pashley, D.P., Johnson, S.J., and Sparks, A.N. (1985). Genetic population structure of migratory moths: the fall armyworm (Lepidoptera: Noctuidae). Ann. Entomol. Soc. Am. 78: 756–762, https://doi.org/10.1093/aesa/78.6.756.Search in Google Scholar

Pavinato, V.A., Martinelli, S., de Lima, P.F., Zucchi, M.I., and Omoto, C. (2013). Microsatellite markers for genetic studies of the fall armyworm, Spodoptera frugiperda. Genet. Mol. Res. 12: 370–380, https://doi.org/10.4238/2013.february.8.1.Search in Google Scholar

Pecina-Quintero, V., Lopez-Edward, J., Prowell, D.P., Groot, A.T., and Rosas-Garcia, M. (2015). Caracterización genética de Spodoptera frugiperda (J.E. Smith) en México usando marcadores AFLP. Southwest. Entomol. 40: 545–553.10.3958/059.040.0313Search in Google Scholar

Pečnikar, Ž.F. and Buzan, E.V. (2013). 20 years since the introduction of DNA barcoding: from theory to application. J. Appl. Genet. 55: 43–45.10.1007/s13353-013-0180-ySearch in Google Scholar PubMed

Pélissié, B., Crossley, M.S., Cohen, Z.P., and Schoville, S.D. (2018). Rapid evolution in insect pests: the importance of space and time in population genomics studies. Cur. Opin. Insect Sci. 26: 8–16, https://doi.org/10.1016/j.cois.2017.12.008.Search in Google Scholar PubMed

Prasanna, B.M., Hu, J.E., Eddy, R., and Peschke, V.M. (Eds.) (2018). Fall armyworm in Africa: a guide for integrated pest management. Centro Internacional de Mejoramiento de Maíz y Trigo, Ciudad de México, México.Search in Google Scholar

Prowell, D.P., McMichael, M., and Silvain, J.F. (2004). Multilocus genetic analysis of host use, introgression, and speciation in host strains of fall armyworm (Lepidoptera: Noctuidae). Ann. Entomol. Soc. Am. 97: 1034–1044, https://doi.org/10.1603/0013-8746(2004)097[1034:mgaohu]2.0.co;2.10.1603/0013-8746(2004)097[1034:MGAOHU]2.0.CO;2Search in Google Scholar

Saitou, N. and Neim, N.M. (1987). The neighbor-joining method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4: 406–425, https://doi.org/10.1093/oxfordjournals.molbev.a040454.Search in Google Scholar PubMed

Saldamando, C.I. and Vélez-Arango, A.M. (2010). Host plant association and genetic differentiation of corn and rice strains of Spodoptera frugiperda Smith (Lepidoptera: Noctuidae) in Colombia. Neotrop. Entomol. 39: 921–929, https://doi.org/10.1590/s1519-566x2010000600012.Search in Google Scholar PubMed

Salinas-Hernández, H. and Saldamando-Benjumea, C. (2011). Haplotype identification within Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae) corn and rice strain from Colombia. Neotrop. Entomol. 40: 421–430.Search in Google Scholar

Slatkin, M. (1987). Gene flow and the geographic structure of natural populations. Science 236: 787–792, https://doi.org/10.1126/science.3576198.Search in Google Scholar PubMed

Smith, M.A., Rodriguez, J.J., Whitfield, J.B., Deans, A.R., Janzen, D.H., Hallwachs, W., and Hebert, P.D.N. (2008). Extreme diversity of tropical parasitoid wasps exposed by iterative integration of natural history, DNA barcoding, morphology, and collections. Proc. Natl. Acad. Sci. USA 105: 12359–12364, https://doi.org/10.1073/pnas.0805319105.Search in Google Scholar PubMed PubMed Central

Stecher, G., Tamura, K., and Kumar, S. (2020). Molecular evolutionary genetics analysis (MEGA) for macOS. Mol. Biol. Evol. 37: 1237–1239, https://doi.org/10.1093/molbev/msz312.Search in Google Scholar PubMed PubMed Central

Tamura, K., Nei, M., and Kumar, S. (2004). Prospects for inferring very large phylogenies by using the neighbor-joining method. Proc. Natl. Acad. Sci. USA 101: 11030–11035, https://doi.org/10.1073/pnas.0404206101.Search in Google Scholar PubMed PubMed Central

Tay, W.T., Meagher, R.L.Jr., Czepak, C., and Groot, A.T. (2023). Spodoptera frugiperda: ecology, evolution, and management options of an invasive species. Annu. Rev. Entomol. 68: 299–317, https://doi.org/10.1146/annurev-ento-120220-102548.Search in Google Scholar PubMed

Tay, W.T., Rane, R.V., Padovan, A., Walsh, T.K., Elfekih, S., Downes, S., Nam, K., d´Alençon, E., Zhang, J., Wu, Y, et al.. (2022). Global population genomic signature of Spodoptera frugiperda (fall armyworm) supports complex introduction events across the Old World. Commun. Biol. 5: 297, https://doi.org/10.1038/s42003-022-03230-1.Search in Google Scholar PubMed PubMed Central

Trisyono, Y.A., Suputa, S., Aryuwandari, V.E.F., Hartaman, M., and Jumari, J. (2019). Occurrence of heavy infestation by the fall armyworm Spodoptera frugiperda, a new alien invasive pest, in corn Lampung, Indonesia. J. Perlindungan Tanaman Indones. 23: 156–160, https://doi.org/10.22146/jpti.46455.Search in Google Scholar

Wang, W., He, P., Zhang, Y., Liu, T., Jing, X., and Zhang, S. (2020). The population growth of Spodoptera frugiperda on six cash crop species and implications for its occurrence and damage potential in China. Insects 11: 639, https://doi.org/10.3390/insects11090639.Search in Google Scholar PubMed PubMed Central

Wu, P., Wu, F., Fan, J., and Zhang, R. (2021). The potential economic impact of the invasive fall armyworm mainly affected crops in China. J. Pest Sci. 94: 1065–1073, https://doi.org/10.1007/s10340-021-01336-9.Search in Google Scholar
Received: 2024-09-04
Accepted: 2025-06-27
Published Online: 2025-09-23

© 2025 the author(s), published by De Gruyter on behalf of the Florida Entomological Society

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

  1. Frontmatter
  2. Research Articles
  3. Parasitism of Halyomorpha halys and Nezara viridula (Hemiptera: Pentatomidae) sentinel eggs in Central Florida
  4. Genetic differentiation of three populations of the fall armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae), in Mexico
  5. Tortricidae (Lepidoptera) associated with blueberry cultivation in Central Mexico
  6. First report of Phidotricha erigens (Lepidoptera: Pyralidae: Epipaschiinae) injuring mango inflorescences in Puerto Rico
  7. Seed predation of Sabal palmetto, Sabal mexicana and Sabal uresana (Arecaceae) by the bruchid Caryobruchus gleditsiae (Coleoptera: Bruchidae), with new host and distribution records
  8. Genetic variation of rice stink bugs, Oebalus spp. (Hemiptera: Pentatomidae) from Southeastern United States and Cuba
  9. Selecting Coriandrum sativum (Apiaceae) varieties to promote conservation biological control of crop pests in south Florida
  10. First record of Mymarommatidae (Hymenoptera) from the Galapagos Islands, Ecuador
  11. First field validation of Ontsira mellipes (Hymenoptera: Braconidae) as a potential biological control agent for Anoplophora glabripennis (Coleoptera: Cerambycidae) in South Carolina
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  19. Biological response of Rhopalosiphum padi and Sipha flava (Hemiptera: Aphididae) changes over generations
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  26. Scientific Notes
  27. Early stragglers of periodical cicadas (Hemiptera: Cicadidae) found in Louisiana
  28. Attraction of released male Mediterranean fruit flies to trimedlure and an α-copaene-containing natural oil: effects of lure age and distance
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  30. Observation of brood size and altricial development in Centruroides hentzi (Arachnida: Buthidae) in Florida, USA
  31. New quarantine cold treatment for medfly Ceratitis capitata (Diptera: Tephritidae) in pomegranates
  32. A new invasive pest in Mexico: the presence of Thrips parvispinus (Thysanoptera: Thripidae) in chili pepper fields
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  34. Examining phenotypic variations in an introduced population of the invasive dung beetle Digitonthophagus gazella (Coleoptera: Scarabaeidae)
  35. Note on the nesting biology of Epimelissodes aegis LaBerge (Hymenoptera: Apidae)
  36. Mass rearing protocol and density trials of Lilioceris egena (Coleoptera: Chrysomelidae), a biological control agent of air potato
  37. Cardinal predation of the invasive Jorō spider Trichophila clavata (Araneae: Nephilidae) in Georgia
  38. Retraction
  39. Retraction of: Examining phenotypic variations in an introduced population of the invasive dung beetle Digitonthophagus gazella (Coleoptera: Scarabaeidae)
https://doi.org/10.1515/flaent-2024-0072
Keywords for this article
DNA; PCR; gene flow; haplotype diversity
Creative Commons
BY 4.0

Articles in the same Issue

  1. Frontmatter
  2. Research Articles
  3. Parasitism of Halyomorpha halys and Nezara viridula (Hemiptera: Pentatomidae) sentinel eggs in Central Florida
  4. Genetic differentiation of three populations of the fall armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae), in Mexico
  5. Tortricidae (Lepidoptera) associated with blueberry cultivation in Central Mexico
  6. First report of Phidotricha erigens (Lepidoptera: Pyralidae: Epipaschiinae) injuring mango inflorescences in Puerto Rico
  7. Seed predation of Sabal palmetto, Sabal mexicana and Sabal uresana (Arecaceae) by the bruchid Caryobruchus gleditsiae (Coleoptera: Bruchidae), with new host and distribution records
  8. Genetic variation of rice stink bugs, Oebalus spp. (Hemiptera: Pentatomidae) from Southeastern United States and Cuba
  9. Selecting Coriandrum sativum (Apiaceae) varieties to promote conservation biological control of crop pests in south Florida
  10. First record of Mymarommatidae (Hymenoptera) from the Galapagos Islands, Ecuador
  11. First field validation of Ontsira mellipes (Hymenoptera: Braconidae) as a potential biological control agent for Anoplophora glabripennis (Coleoptera: Cerambycidae) in South Carolina
  12. Field evaluation of α-copaene enriched natural oil lure for detection of male Ceratitis capitata (Diptera: Tephritidae) in area-wide monitoring programs: results from Tunisia, Costa Rica and Hawaii
  13. Abundance of Megalurothrips usitatus (Bagnall) (Thysanoptera: Thripidae) and other thrips in commercial snap bean fields in the Homestead Agricultural Area (HAA)
  14. Performance of Salvinia molesta (Salviniae: Salviniaceae) and its biological control agent Cyrtobagous salviniae (Coleoptera: Curculionidae) in freshwater and saline environments
  15. Natural arsenal of Magnolia sarcotesta: insecticidal activity against the leaf-cutting ant Atta mexicana (Hymenoptera: Formicidae)
  16. Ethanol concentration can influence the outcomes of insecticide evaluation of ambrosia beetle attacks using wood bolts
  17. Post-release support of host range predictions for two Lygodium microphyllum biological control agents
  18. Missing jewels: the decline of a wood-nesting forest bee, Augochlora pura (Hymenoptera: Halictidae), in northern Georgia
  19. Biological response of Rhopalosiphum padi and Sipha flava (Hemiptera: Aphididae) changes over generations
  20. Argopistes tsekooni (Coleoptera: Chrysomelidae), a new natural enemy of Chinese privet in North America: identification, establishment, and host range
  21. A non-overwintering urban population of the African fig fly (Diptera: Drosophilidae) impacts the reproductive output of locally adapted fruit flies
  22. Fitness of Bactrocera dorsalis (Hendel) (Diptera: Tephritidae) on four economically important host fruits from Fujian Province, China
  23. Carambola fruit fly in Brazil: new host and first record of associated parasitoids
  24. Establishment and range expansion of invasive Cactoblastis cactorum (Lepidoptera: Pyralidae: Phycitinae) in Texas
  25. A micro-anatomical investigation of dark and light-adapted eyes of Chilades pandava (Lepidoptera: Lycaenidae)
  26. Scientific Notes
  27. Early stragglers of periodical cicadas (Hemiptera: Cicadidae) found in Louisiana
  28. Attraction of released male Mediterranean fruit flies to trimedlure and an α-copaene-containing natural oil: effects of lure age and distance
  29. Co-infestation with Drosophila suzukii and Zaprionus indianus (Diptera: Drosophilidae): a threat for berry crops in Morelos, Mexico
  30. Observation of brood size and altricial development in Centruroides hentzi (Arachnida: Buthidae) in Florida, USA
  31. New quarantine cold treatment for medfly Ceratitis capitata (Diptera: Tephritidae) in pomegranates
  32. A new invasive pest in Mexico: the presence of Thrips parvispinus (Thysanoptera: Thripidae) in chili pepper fields
  33. Acceptance of fire ant baits by nontarget ants in Florida and California
  34. Examining phenotypic variations in an introduced population of the invasive dung beetle Digitonthophagus gazella (Coleoptera: Scarabaeidae)
  35. Note on the nesting biology of Epimelissodes aegis LaBerge (Hymenoptera: Apidae)
  36. Mass rearing protocol and density trials of Lilioceris egena (Coleoptera: Chrysomelidae), a biological control agent of air potato
  37. Cardinal predation of the invasive Jorō spider Trichophila clavata (Araneae: Nephilidae) in Georgia
  38. Retraction
  39. Retraction of: Examining phenotypic variations in an introduced population of the invasive dung beetle Digitonthophagus gazella (Coleoptera: Scarabaeidae)
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