Spodoptera frugiperda, a member of the Lepidoptera family Noctuidae, was first recognized as a harmful pest in Georgia in 1797 Smith and Abbott (1797). The United States experienced multiple "marching-worms" epidemics between 1856 and 1928 Glover (1856). After 1928, expansion of fall armyworm (FAW) into new areas was not widely documented until it established itself as a serious pest and destroyed crops in several southern regions. S. frugiperda is invasive and one of the worst pests to maize in the America; and recently native to South tropical and subtropical zones of America. Biology and distribution of S. frugiperda is affected by low temperatures Schlemmer (2018). This insect has spread to China, Africa, and the Tropics, where it represents a significant threat to food security. It was established that FAW had spread to nearly all 44 sub-Saharan countries in the years 2016 to 2018 (Goergen et al. 2016; Guo et al. 2018; Sharanabasappa et al. 2018). This included Asian nations like India, Thailand, Bangladesh, and Myanmar.
Infestations of S. frugiperda larvae were first detected in Jiangcheng county cornfields (Yunnan province, China) on January 11 2019. Except for Xinjiang, Qinghai, and Northeastern China, the existence of S. frugiperda was quickly confirmed in 26 other provinces (Jiang et al. 2019; Yan et al. 2019; Zhang et al.2019; Jing et al. 2020).
When conditions are less favorable for survival, this species which lacks the diapause feature, must start a new set of migratory flights (Luginbill 1928; Westbrook et al. 2016). Contrary to what was previously believed, at normal temperatures, the average number of pest species declined with increasing altitude and latitude. A successful climatic adaptation can increase chances for a species to finish its life cycle and is also a major factor in quick global spread of the FAW. However, the literature on the heat resistance of the FAW is still poorly understood; studies have shown that population development is impeded at extremely high temperatures (Zhang et al. 2020).
The objectives of this research include:
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To assess the current distribution range of S. frugiperda in the world, considering climate variables and ecological factors.
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To investigate the potential impacts of climate change on the habitat suitability of S. frugiperda with particular attention on rising temperatures and fluctuating precipitation patterns.
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To predict the future distribution range of S. frugiperda in the years 2021–2040, and 2080–2100 under different Representative Concentration Pathway (climate) scenarios and to compare the differences between scenarios.
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To analyze the key climatic variables and ecological factors resulting in S. frugiperda invasiveness patterns with their potential for wide-scale alteration of food security in newly invaded countries.
Previous Global Climate Change Studies of S. frugiperda
The potential worldwide distribution of FAW under present and future climate change scenarios in 2050 and 2070 under Shared Socioeconomic Pathway (SSP) 1-2.6 and SSP5-8.5 emission scenarios using 19 bioclimatic variables through Maximum Entropy (MaxEnt) niche modeling was previously investigated by Ramasamy et al. (2022). During running and testing they discovered that the area under the curve (AUC) had values of 0.915 for SSP1-2.6 and 0.910 for SSP5-8.5. The contributions percentages were 42.6%, 22.4%, and 10%, for Annual Precipitation, Annual Mean Temperature and Isothermality respectively, which were the most influential variables. Recent CMIP6 models show North America, Africa and Asia are more suitable for FAW under future climatic conditions. The SSP1-2.6 and SSP5-8.5 scenarios predict that the global suitability of FAW will rise by 4.49% and 8.33% respectively in comparison to that of current climate conditions. Under the SSP5-8.5 scenario, the multimodel ensemble estimated the highest probability of FAW spread by 2050 and 2070.
The CLIMEX model used to predict the annual and seasonal suitable distribution of FAW used HYSPLIT, a numerical trajectory model to simulate probability of the FAW invasion of Europe via wind-driven dispersion Wang et al. (2023). The results demonstrated that there was a highly significant degree of consistency in the risk of FAW invasion (P < 0.001) between years. Spain and Italy had the largest probability of invasion, with 39.08% and 32.20% of effective landing places respectively and coastal regions were most suited for the invasion of FAW.
The global potential for the spread of the species and its associated impacts on major host plants was studied by Zacarias et al. (2020). According to simulations, there is a significant climatic potential in the future for the species to expand, with increased probability between 12 and 44% between the United States and Canada, Sub-Saharan Africa, and central Europe.
The current research projects the effects of climate change on future appropriateness for the growth and range of FAW and to emphasize the risk of damage caused by the pest under both the present and the future scenario investigated by Ramirez-cabral et al. (2017). By the known distribution of the species and the CliMond meteorological database, the model used two general circulation models (GCMs), CSIRO Mk3.0 and MIROC-H, in 2050 and 2100 under the A2 Special Report on Emissions Scenarios (SRES). With the exception of southern Brazil, Paraguay, Uruguay, and northern Argentina, which imply high future levels of danger, the data demonstrate shifts in suitability and risk across North America, with an increase in the northern hemisphere and declines or extinction in the southern hemisphere. In comparison to the current risk, the two GCMs predicted that the low-risk group would increase by 40% by 2050 and 23% by 2100, while the medium- and high-risk categories would decrease by > 50% and > 39%, respectively.
Previous Climate Change Studies of S. frugiperda in China
The probable distribution of S. frugiperda in China under climate change was predicted by Jiang et al. (2022), the research findings indicated that South China, East China, Central China, and eastern Southwest China occupy high suitability areas. The main environmental variable influencing the possible spread of S. frugiperda were bio11 (Mean Temperature in the Coldest Quarter) and bio12 (Annual Precipitation).
An explanation of how the spread of S. frugiperda has been impacted by climate change was provided by Cai et al. (2021). They chose bioclimatic variables and used four climate change scenarios to predict habitat suitability in China based on S. frugiperda occurrences using Geographic Information Systems (GIS) and Maximum Entropy models (MaxEnt). They found that: (1) the mean area under the curve (AUC) values for both initial and final models were greater than 0.978, indicating high inter-model accuracy; (2) the favorable environmental factors governing habitat suitability were bio18 (Precipitation of the Warmest Quarter), bio4 (Temperature Seasonality), bio1 (Annual Mean Temperature), and biol5 (Precipitation Seasonality); and (3) the highly suitable regions for S. frugiperda were primarily distributed in Anhui, Jiangsu, most of Henan and Guangxi, along with southeastern and northern Zhejiang, central and southern Shaanxi provinces.
Previous Climate Change Studies of S. frugiperda in Africa
The CLIMEX model used to assess the global invasion hazard of FAW in Africa Paudel Timilsena et al. (2022). The results showed that almost all the countries in eastern and central Africa, as well as a sizable fraction of those in western Africa, that FAW can establish itself under the current conditions. Climate restrictions like heat and arid weather may limit the expansion of FAW to the South and North. According to future predictions the invasive range of FAW will shift southward and northward regions towards the equator. It is expected that a substantial area of central and eastern Africa will have suitable environment for FAW.
Previous Climate Change Studies of S. frugiperda in the Tropics
The effects of climatic change on armyworm attacks of maize was investigated by Nurzannah et al. (2020). In this study, multiple linear regression analyses were used. They found that regional impact data and climate factor data acted as independent and dependent variables, respectively. Rainfall is one climate component that significantly affects the habitat of the impacted area. The countries of Laos, Vietnam, Thailand, Malaysia, Cambodia, Philippines, Indonesia, Solomon Islands, Papua New Guinea, and Sri Lanka are included in our classification of the Tropics for this study.