*2.3. Statistical Analysis*

In this study, SPSS v23 (IBM Corp., Armonk, NY, USA), and RStudio software (RStudio, PBC, Vienna, Austria) were used for statistical analysis. Trend analyses of the climate variables (SPEI, Precipitation, Temperature) over the last 71 years (1950–2020) at the studied wild blueberry fields (Airport/Baxter and Maine) were conducted using a Mann–Kendall trend test and Sen's slope estimator using the XRealStats (Addinsoft, New York, NY, USA) add-on in Microsoft Excel. The "pheno" package in RStudio was used to analyze the forward (UF) and backward (UB) curves of the sequential Mann–Kendall test statistics. Trend analyses of the EVI and yield over the last 21 years (2000–2020) at the studied wild blueberry fields (Airport/Baxter and Maine) were conducted using a Mann–Kendall trend test and Sen's slope estimator using the XRealStats tool. To assess the statistical significance of the Mann-Kendall trend analysis, the significance level (α) was set to 0.05.

A Pearson correlation analysis was conducted between different temporal scales of SPEI and EVI and yield to understand the drought impact on vegetation (EVI) and yield at different temporal scales using SPSS v23. To assess the statistical significance of the Pearson correlation analysis, the significance level (α) was set to 0.05.

To understand the effects of short- to long-term water conditions (SPEI\_1\_Year to SPEI\_4\_Year) on the EVI and NDVI (average of the growing season: May–September) for the studied wild blueberry fields over 21 years (2000–2020), linear (in the form of a + bx) and non-linear (in the form a + bx + cx 2) regression analyses were also conducted using SPSS v23. A similar analysis was conducted to understand the short- to long-term impact of water conditions (indicated by SPEI\_1\_Year to SPEI\_4\_Year) on the yield of the studied wild blueberry fields. We determined the statistical significance of the relationship using the coefficient of determination and its significance (α) at *p* < 0.05.
