Fig 1.
Study areas map showing the African continent boundaries.
Fig 2.
Flowchart of the hierarchical methodology for the analysis of fall armyworm phenology.
Table 1.
A complete set of mathematical model equations utilized in ILYCM software to develop S. frugiperda phenology for each life stage.
Table 2.
Mean development times (days) of immature stages and senescence times (days) of adult life stages of S. frugiperda at different constant temperatures in the lab.
R2—Coefficient of determination and AIC -Akaike Information Criterion.
Fig 3.
Spodoptera frugiperda (a) egg, (b) larva, and (c) pupa development rates as a function of temperature, respectively fitted by Logan-5, Hilber & logan 2, and Logan 1, respectively, at each developmental stage. The standard deviation is depicted by the blue bars, while the blue points indicate the experimental data. The red broken lines represent the fitted linear models, whereas the solid lines represent the fitted non-linear models. Upper and lower 95% confidence intervals are depicted by the broken blue lines above and below, respectively.
Table 3.
Estimated parameters of the Logan-5, Hilber & logan 2, and Logan 1 models that were used to estimate how temperature affects the rate of development of immature S. frugiperda that were raised at different constant temperatures.
R2—Coefficient of determination, AIC—Akaike Information Criterion and df–degree of freedom.
Fig 4.
Temperature-dependent death rates of S. frugiperda immature stages fitted to Wang1, Wang 2 and Gaussian with log models: (a) egg; (b) larva; (c) pupa. The experimental data is blue. Solid red lines represent non-linear models and broken blue lines the upper and lower 95% confidence intervals.
Table 4.
Estimated parameters of the Wang 2, Wang 1, and Gaussian with log models that were used to estimate how temperature affects the mortality rate of immature S. frugiperda raised at different constant temperatures.
R2—Coefficient of determination, AIC—Akaike Information Criterion and df–degree of freedom.
Fig 5.
Model fitting to determine the relationship between temperature and S. frugiperda female fecundity, and adult senescence: (a) female senescence rates fitted to Exponential simple function; (b) male senescence rates fitted to Hilber &Logan 3 function; c) cumulative fecundity fitted to Simple gaussian; and (d) mean fecundity per female fitted to Taylor function 1. The blue points represent the experimental data with bars representing the standard deviation. The solid red lines represent non-linear models. The broken blue lines above and below represent the upper and lower 95% confidence intervals.
Table 5.
Estimated parameters of the relative oviposition of S. frugiperda.
R2—Coefficient of determination, AIC—Akaike Information Criterion, and df–degree of freedom.
Table 6.
Estimated parameters of the total oviposition of S. frugiperda.
R2—Coefficient of determination, AIC—Akaike Information Criterion and df–degree of freedom.
Table 7.
Estimated parameters of Hilber & Logan3 and Exponential simple fitted to determine the relationship between temperature and adult senescence S. frugiperda reared at different constant temperatures.
R2—Coefficient of determination, AIC—Akaike Information Criterion, and df–degree of freedom.
Fig 6.
Observed and simulated S. frugiperda life stage frequencies to test temperature-dependent development models for development, survival, and reproduction.
The lines reflect phenology model-simulated values for each life stage, whereas the dots represent experimental values from variable temperatures.
Table 8.
Simulated life table parameters of S. frugiperda reared at five constant temperatures.
The intrinsic rate of increase (rm), gross reproduction rate (GRR), net reproduction rate (Ro), mean generation time (Tc in days), doubling time (Dt) in days, and finite rate of increase (λ).
Table 9.
Comparative analysis of area changes for fall armyworm risk indices under current, RCP 2.6, and RCP 8.5 climate scenarios for 2050 and 2070.
Fig 7.
Illustration of the activity index (AI) of the fall armyworm in Africa for the current scenario, 2050 and 2070, under two contrasting climate change scenarios: RCP 2.6 (more ambitious climate mitigation) and RCP 8.5 (more pessimistic climate change).
The value ranges from high (blue), medium (green) and low (orange).
Fig 8.
Illustration of the Establishment Risk Index (ERI) of the fall armyworm in Africa for the current scenario, 2050 and 2070, under two contrasting climate change scenarios: RCP 2.6 (more ambitious climate mitigation) and RCP 8.5 (more pessimistic climate change).
The value ranges from high (blue), medium (green) and low (orange).
Fig 9.
Illustration of the Generation Index (GI) of the fall armyworm in Africa for the current scenario, 2050 and 2070, under two contrasting climate change scenarios: RCP 2.6 (more ambitious climate mitigation) and RCP 8.5 (more pessimistic climate change).
The value ranges from high (blue), medium (green) and low (orange).