# Monitoring Changes in the Enhanced Vegetation Index to Inform the Management of Forests
## 3 Results
### EVI Changes Throughout the Study Area
With respect to negative breaks, the difference between protected (median = \(-\)765.6, mean = \(-\)854.3, \(n\) = 470) and non-protected forests (median = \(-\)754.6, mean = \(-\)829.5, \(n\) = 11,499) was not significant. Attribution of negative breaks to disturbance data (remote sensing derived) was conducted with varying degrees of success depending on the data source used (Table A3). For instance, only 16% of detected negative breaks could be matched (in space and in time using time of break 95% CIs) with forest harvest pixels, and less than 1% of breaks could be matched with insect damage (moderate and severe tree infestation and mortality) (\(h\) = 0.05 heading in Table A3). When using CanLaD (fire and harvest), a 28% match with negative breaks was achieved and with GFC (a disturbance dataset with no labels) the matching went up to 60%. Thus, in the best of cases, about 40% of the negative breaks found in this study could not be matched to disturbance data. This suggests that many of the negative EVI breaks are likely associated with low or moderate non-stand replacing disturbances or other factors (i.e., soil conditions) that left a strong enough signal that was detected with EVI. The bfastclassify algorithm revealed that 27.8% of forest pixels had statistically significant trends (Table 3). Similarly, about 14.6% of forest pixels experienced greening (monotonic increasing trends without breaks, MIG) while 2.2% experienced browning (monotonic decreasing trends without breaks, MDB). About 5% of forest pixels showed interruption trends (increasing trend with a negative break, IInb) and 5% showed reversal trends (browning to greening, RBG). About 2.6% of forest pixels showed interruption trends characterized by a decreasing trend with a positive break (IDpb). Breaking down the results by protection status, 15% of all non-protected forest pixels showed greening trends (MIG) compared to 8.4% of protected forest pixels. Similarly, MDB trends represent 2.2% of trends in non-protected areas compared to 1.6% in protected ones. Furthermore, 5.3% of all non-protected forest pixels showed IInb trends while only 2.4% of protected forest pixels showed this trend. Likewise, 5.5% of all non-protected forest pixels showed RBG trends compared to 1.4% of all protected forest pixels. That is, non-protected forests showed about twice the percentage of IInb trends and about four times the percentage of RBG trends compared to protected forests (5.3% vs. 2.4% and 5.5% vs. 1.4% respectively). All other trend types including monotonic increasing trends (greening) with positive breaks (MIGpb), monotonic decreasing trends (browning) with negative breaks (MDBnb), and interruption trends characterized by decreasing trends with positive breaks (IDpb) represented <1% of all forest pixels (Table 3). In terms of spatial distribution, similar to the breaks, most of the statistically significant trends occurred in the eastern half of the AGPE (Figure 4). Browning trends were mostly detected in the northeast quadrant while greening trends were more evenly distributed. There was a noticeable concentration of interruption trends (type IInb) in the northwest quadrant of the AGPE.