## 3 Results
### Spatial and Statistical Analysis
As the study continued, the slopes of the land surface where there is forest cover, were identified using functions of the GIS program. The data were converted into Microsoft Excel tables. Calculations of what percentage of the forest area was made up of certain slopes of land surface in individual administrative units were performed. A correlation analysis was performed as the study of statistical links between slopes and changes in forest areas continued (Table 17). Indicators:  
share of the area occupied by the forest cover (as a percentage) in the areas with the respective slope;  
slope of the land surface. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Elderships**} & \multicolumn{2}{c}{**2 nd Half of the**} & \multicolumn{2}{c}{**1 st Half of the**} & \multicolumn{2}{c}{**2 nd Half of the**} \\  & \multicolumn{2}{c}{**19 th Century**} & \multicolumn{2}{c}{**20 th Century**} & \multicolumn{2}{c}{**20 th Century**} \\ \cline{2-7}  & **rij** & \(p\)**-Value** & **rij** & \(p\)**-Value** & **rij** & \(p\)**-Value** \\ \hline Erzvilkas & \(-0.72\) & \(0.03\) & \(-0.56\) & \(0.11\) & \(-0.66\) & \(0.05\) \\ Girdziai & \(-0.75\) & \(0.02\) & \(-0.66\) & \(0.05\) & \(-0.19\) & \(0.63\) \\ Juodaičiai & \(-0.86\) & \(0.03\) & \(-0.85\) & \(0.03\) & \(-0.76\) & \(0.08\) \\ Jurbarkai & \(-0.91\) & \(0.00\) & \(-0.92\) & \(0.00\) & \(0.51\) & \(0.16\) \\ Jurbarkas city & \(-0.66\) & \(0.05\) & \(0.27\) & \(0.48\) & \(0.05\) & \(0.90\) \\ Raudone & \(-0.59\) & \(0.09\) & \(0.90\) & \(0.00\) & \(0.91\) & \(0.00\) \\ Seredzius & \(-0.62\) & \(0.08\) & \(0.69\) & \(0.04\) & \(0.69\) & \(0.04\) \\ Skirsnemune & \(-0.59\) & \(0.09\) & \(-0.40\) & \(0.29\) & \(0.72\) & \(0.06\) \\ Smalininkai & \(-0.62\) & \(0.08\) & \(-0.81\) & \(0.01\) & \(-0.91\) & \(0.00\) \\ Simkačiai & \(0.24\) & \(0.54\) & \(-0.70\) & \(0.04\) & \(-0.70\) & \(0.04\) \\ Veliuona & \(-0.58\) & \(0.10\) & \(0.22\) & \(0.58\) & \(0.28\) & \(0.47\) \\ Viešile & \(0.90\) & \(0.00\) & \(0.84\) & \(0.00\) & \(-0.54\) & \(0.13\) \\ Jurbarkas Distr. & \(-0.82\) & \(0.01\) & \(0.02\) & \(0.95\) & \(0.82\) & \(0.01\) \\ \hline \hline \end{tabular}
\end{table} 
Table 17: Correlation analysis results between slope and forest cover areas. Figure 19: Map of slopes of Jurbarkas District correlating/non-correlating with changes in forest cover in the 19 th–21 st centuries. In order to visualize the results of the research, a map of the correlation analysis results was created using the GIS program (Figure 20). It shows the elderships of Jurbarkas District and their soil productivity scores. Elderships with very strong, strong, and moderate correlations and \(p\)-values \(\leq\) 0.05 are marked in yellow. Quite different results were obtained when researching the links between forest areas and surface slopes. No statistically significant correlations between indicators were found in the eastern part of Jurbarkas District in the 19 th century (Table 17). Figure 20 shows that there are quite strong correlations between the areas of forest cover and the land surface slopes in the elderships located in the western part. Forests grow on plains in almost all of them (with the exception of Viesvile eldership) because as the slope increases, forest areas decrease. Figure 11 shows that forest cover is mostly absent along the rivers. Viesvile eldership is unique--a positive correlation is observed in it--the forest areas increase with the increase in the slope of the territory. This eldership is located in another state where a completely different forest management and land management strategy is implemented. Five elderships balance on the limit of statistical significance (0.08 \(\leq\)\(p\)-value \(\leq\) 0.10), and the correlation coefficients in them vary 1 0.58 \(\leq\) r\({}_{\overline{\mathrm{ij}}}\)\(\leq\) 1 0.621. Simkaicaia eldership stands out, with \(p\)-value = 0.24. Taking the entire Jurbarkas District for the study, we get r = \(-\)0.82, \(p\)-value = 0.01.