## 3 Results
### Temperature and Precipitation
For the AST, the historical temperature ranges between 6.14 \({}^{\circ}\)C and 12.14 \({}^{\circ}\)C, while it is 9.22 \({}^{\circ}\)C to 15.32 \({}^{\circ}\)C degrees Celsius for CanESM2 and 10.76 \({}^{\circ}\)C to 16.61 \({}^{\circ}\)C degrees Celsius for CanESM5 (Figure 2B). It is evident that both climate change models project temperature distributions significantly higher than historical values. This suggests a substantial temperature increase in the study area according to two different climate change models, each based on distinct scenarios. The temperature rise associated with climate change can have complex and diverse effects on pesticide use in agriculture, impacting factors such as pest populations, pesticide efficacy, environmental concerns, and the overall sustainability of pest management practices [37, 38, 39]. A more comprehensive scrutiny of the \begin{table}
\begin{tabular}{c c c c c c c} \hline \multirow{2}{*}{**Index**} & \multicolumn{3}{c}{**Total Precipitation (mm)**} & \multicolumn{3}{c}{**Total Precipitation (mm)**} \\  & **Historical** & **CanESM2** & **CanESM5** & **Historical** & **CanESM2** & **CanESM5** \\ \hline Minimum & 616.0 & 527.0 & 566.3 & 6.1 & 9.2 & 10.8 \\
1 st Quantile (Q1) & 718.4 & 636.1 & 683.3 & 9.2 & 12.5 & 13.8 \\ Mean & 754.7 & 662.9 & 704.4 & 10.6 & 13.6 & 15.0 \\
3 rd Quantile (Q3) & 825.3 & 710.7 & 765.3 & 11.4 & 14.5 & 15.8 \\ Maximum & 987.4 & 857.8 & 904.2 & 12.1 & 15.3 & 16.6 \\ Interquartile (IQR) & 106.9 & 74.6 & 82.1 & 2.1 & 2.0 & 2.0 \\ \hline \end{tabular}
\end{table} 
Table 1: Summary statistics for total precipitation (mm) and average seasonal temperature (AST) for historical records and projections by climate change models CanESM2 and CanESM5. historical and projected data reveals substantial deviations. Specifically, when comparing the historical AST to CanESM2 and CanESM5, the disparities are pronounced, amounting to 28.67% and 41.5% (respectively) relative error. Moreover, an analysis of the AST distribution unveils a noteworthy pattern. The first quartile (Q1) associated with the AST projected by climate change models surpasses the Q3 value linked to historical records. Indeed, less than 25% of the total AST values projected by climate change models align with the values recorded historically. AST exhibits a more substantial increase in CanESM5 than CanESM2. Consequently, the average AST value associated with CanESM5 surpasses that of CanESM2 by approximately 10%. Table 2 shows the ANOVA results for comparing historical temperature and precipitation data with climate projections from the CanESM2 and CanESM5 models. These results reveal significant differences between historical observations and the projections from both models, as well as notable discrepancies between them, providing insights into how each model interprets future climate conditions. For temperature, the F-statistics and \(p\)-values indicate significant differences between historical data and CanESM2 and CanESM5 projections. When comparing the historical temperature data to CanESM2, the F-statistic is 1057.834, with a \(p\)-value of 4.67 \(\times\) 10\({}^{-143}\). This implies that CanESM2 anticipates a substantial departure from historical temperature trends. The significant variation points to likely increases in temperature as forecasted by CanESM2, which may be attributed to the model's assumptions regarding the impact of greenhouse gases and other climate factors. The comparison between historical temperature data and CanESM5 shows an even higher F-statistic of 2105.13 with an extremely small \(p\)-value of 4.14 \(\times\) 10\({}^{-215}\). This suggests that CanESM5 projects even greater temperature shifts than CanESM2, highlighting that the CanESM5 model foresees more extreme temperature changes. In this case, the higher F-statistic suggests that CanESM5 is more sensitive to climate drivers, possibly incorporating more updated factors or feedback mechanisms that result in larger temperature projections.