Modeling Seasonal Migration of Fall Armyworm Moths
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Int J Biometeorol (2016) 60:255–267 DOI 10.1007/s00484-015-1022-x ORIGINAL PAPER Modeling seasonal migration of fall armyworm moths J. K. Westbrook1,4 & R. N. Nagoshi2 & R. L. Meagher2 & S. J. Fleischer3 & S. Jairam1 Received: 18 September 2014 /Revised: 15 May 2015 /Accepted: 23 May 2015 /Published online: 5 June 2015 # ISB (outside the USA) 2015 Abstract Fall armyworm, Spodoptera frugiperda (J.E. (for locations which captured ≥10 moths), which on average Smith), is a highly mobile insect pest of a wide range of host indicated that the model simulated first immigration 2 weeks crops. However, this pest of tropical origin cannot survive before first captures in pheromone traps. The results contrib- extended periods of freezing temperature but must migrate ute to knowledge of fall armyworm population ecology on a northward each spring if it is to re-infest cropping areas in continental scale and will aid in the prediction and interpreta- temperate regions. The northward limit of the winter- tion of inter-annual variability of insect migration patterns breeding region for North America extends to southern re- including those in response to climatic change and adoption gions of Texas and Florida, but infestations are regularly re- rates of transgenic cultivars. ported as far north as Québec and Ontario provinces in Canada by the end of summer. Recent genetic analyses have charac- Keywords Dispersal . HYSPLIT . Insect . Lepidoptera . terized migratory pathways from these winter-breeding re- Spodoptera frugiperda . Corn-strain gions, but knowledge is lacking on the atmosphere’srolein influencing the timing, distance, and direction of migratory flights. The Hybrid Single-Particle Lagrangian Integrated Tra- Introduction jectory (HYSPLIT) model was used to simulate migratory flight of fall armyworm moths from distinct winter-breeding Fall armyworm, Spodoptera frugiperda (J.E. Smith), is a source areas. Model simulations identified regions of domi- highly mobile insect pest of a wide range of host crops nant immigration from the Florida and Texas source areas and (Luginbill 1928; Sparks 1979). Unlike numerous other mi- overlapping immigrant populations in the Alabama–Georgia grant species, fall armyworm does not possess a capability and Pennsylvania–Mid-Atlantic regions. This simulated mi- to enter diapause, a dormant state which allows insects to gratory pattern corroborates a previous migratory map based survive extended periods of inhospitable conditions including on the distribution of fall armyworm haplotype profiles. We extreme cold or drought (Luginbill 1928; Sparks 1979). Lack- found a significant regression between the simulated first ing a diapause trait, this pest of tropical origin must begin a week of moth immigration and first week of moth capture new series of northward migratory flights each spring if it is to re-infest a succession of cropping areas in the temperate mid- latitude zone (Luginbill 1928). Long-distance migration of fall * J. K. Westbrook armyworm moths and many other crop pests benefits from [email protected] strong and persistent wind patterns (Drake and Gatehouse 1995). Southern Texas and southern Florida are the purported northern-most winter-breeding areas available to fall army- 1 USDA-ARS, College Station, TX, USA worm populations (Luginbill 1928; Snow and Copeland 2 USDA-ARS, Gainesville, FL, USA 1969). However, by the end of the growing season in late 3 Pennsylvania State University, State College, PA, USA summer, fall armyworm infestations are regularly reported as 4 Insect Control and Cotton Disease Research Unit, USDA, ARS, far north as Ontario and Québec, Canada (Rose et al. 1975; SPARC, 2771 F & B Road, College Station, TX 77845-4966, USA Mitchell et al. 1991). 256 Int J Biometeorol (2016) 60:255–267 Insect migration flights have been simulated by atmospher- each area, but there are reproducible differences in their rela- ic simulation models such as Hybrid Single-Particle Lagrang- tive proportions, particularly with respect to the ratio of the h2 ian Integrated Trajectory (HYSPLIT) (Draxler and Hess 1997, and h4 haplotypes. Specifically, comparisons based on sur- 1998;Draxler1999; Draxler and Rolph 2013), GenSim veys over multiple years and locations showed that the CS (Rochester et al. 1996), and Nuclear Accident Model populations in Florida (identified here as the FLA population) (NAME) (Chapman et al. 2012). The HYSPLIT model has displayed an h4/h2 ratio consistently greater than 1.5, while simulated dispersal of boll weevils (Anthonomus grandis populations in Texas (identified here as the TEX population) Boheman) in Texas (Kim et al. 2010; Westbrook et al. 2011) were associated with a ratio less than 0.5 (Nagoshi et al. and migratory trajectories of corn earworms [Helicoverpa zea 2007a, b, 2008). (Boddie)] in the central USA (Westbrook 2008). Similar stud- This ability to distinguish fall armyworm from Texas (TX) ies have been conducted to investigate how synoptic weather and Florida (FL) provides a method for defining the migration conditions, wind trajectories, and atmospheric dispersion af- pathways from these winter-breeding source locations fect the frequency, intensity, and displacement of migratory (Fig. 1). As a proof of concept, Nagoshi et al. (2008)showed flights of noctuid moths in North America (Lingren et al. that fall armyworm isolated from Georgia (GA) closely resem- 1994; Westbrook et al. 1995, 1997), Europe (Chapman et al. bled those from FL, while those in Alabama (AL), Mississippi 2012),Australia(Rochesteretal.1996; Gregg et al. 2001), (MS), and Louisiana (LA) were similar to the TX profile. and Asia (Feng et al. 2009). Although trap data and insect Subsequent studies demonstrated that migration from TX is scouting data have been used to validate migration models, the primary source of fall armyworm infestations west of the confirming these relationships is often problematic because of Appalachian Mountain Range, while the FL migration is the difficulty in identifying the original source of suspected largely limited to the states located on the Atlantic coast immigrants. When source areas can be unambiguously deter- (Nagoshi et al. 2009, 2012). Ambiguous haplotype profiles, mined, as was the case in one study where corn earworm a result expected from the mixing of the Florida and Texas moths were marked naturally by citrus pollen, strong correla- populations, are limited to locations within the states of AL– tions were found between the extrapolated flight paths and GA in the southeast and the Pennsylvania (PA)–Mid-Atlantic synoptic wind trajectories (Lingren et al. 1994; Westbrook region of the eastern seaboard. These results are remarkably et al. 1998a, b). Early studies based on the timing of trap consistent with earlier descriptions based on inferences from captures or synoptic wind patterns provided a broad picture the timing of fall armyworm appearances in different locations of fall armyworm migration but with only limited resolution (reviewed in Nagoshi and Meagher 2008). These indicated a (Mitchell 1979). Migration estimates have been compared northward movement from TX into Oklahoma (OK) and the with general patterns of moth captures in traps or field collec- High Plains states and northeastward flow from southern TX tions of eggs or larvae (i.e., immature stages of fall army- that follows the Coastal Plain into the Mississippi and Ohio worm) (Luginbill 1928; Snow and Copeland 1969;Hartstack River valleys (Luginbill 1928;Pairetal.1986). Populations in et al. 1982). Without a natural or synthetic mark, it is difficult southern FL appear to migrate into GA by June, continuing to identify particular source areas that contribute to immigra- east of the Appalachian Mountains into South Carolina (SC) tions. A direct method is needed for identifying the winter- by July, and likely continue northward along the Atlantic breeding origin of migrant moths that allows extrapolation of Coastal Plain (Luginbill 1928; Snow and Copeland 1969). migratory pathways for the fall armyworm subpopulation. These descriptions are also generally consistent with move- Genetic markers have been developed that can distinguish ments expected from average synoptic meteorological condi- fall armyworm subpopulations (Nagoshi et al. 2007b). Fall tions (Mitchell et al. 1991;Roseetal.1975; Westbrook and armyworm can be subdivided into two behaviorally distinct Sparks 1986) and the geographical distribution of subpopula- but morphologically identical strains that were initially iden- tions that differed with respect to disease or pesticide resis- tified by differences in plant host distribution, hence their tance (Young 1979;Pitre1988; Fuxa 1987). The results sup- designation as rice-strain (RS) and corn-strain (CS) (Pashley port the use of haplotype ratios as a natural marker of the TEX et al. 1985, 1987; Pashley 1986, 1988). Polymorphisms in the and FLA fall armyworm populations that can be used to val- mitochondrial cytochrome oxidase I (COI) gene provide a idate simulation models of migration on a continental scale. convenient and accurate marker for strain identity based on Thegoalofthisstudywastodevelopaseasonalfallarmy- correlations with behavioral differences (Levy et al. 2002;Lu worm migration model that accounts for the phenological de- and Adang 1996; Meagher and Gallo-Meagher 2003; Prowell velopment of corn host plants and fall armyworm populations et al. 2004). and seasonal (multi-generational) migration of fall armyworm The CS population can be further subdivided