Assessing the effects of human settlement proximity on tree health using visual symptoms of tree ill health in Mgwashi Ward, Tanzania

This study aimed to assess the impact of human settlement proximity on tree health within the Mgwashi ward of Tanzania using visual indicators of ill tree health. The study was conducted over eight days in November of 2024. Eight transects, each 100 meters apart, were laid within the study area, extending from human settlement boundaries into forested areas. Each transect contained five 10 X 10-meter plots located at 20-meter intervals extending from human settlements into forested areas. Within each plot, the species of each tree was identified, and the health of each tree was analyzed using a set of visual indicators of ill tree health including defoliation scores, leaf abnormalities, and physical damage. In total, 724 trees were observed, with 695 showing damage as indicators of ill tree health (95.99%). In total, 63 known species were represented, with 62 showing individuals with signs of damage as indicators of ill tree health. Similar proportions of trees located at all measured distances from human settlements showed defoliation, physical damage, and leaf abnormalities. The results of a generalized linear model (GLM) showed no significant relationship between the extent of physical damage and distance from human settlement (R2 = 0.0024, F(1, 703) =1.678, p = 0.196). Likewise, no significant relationship was shown between the extent of defoliation and distance from human settlement (R2 = 0.0013, F(1, 703) = 0.9426, p = 0.3319). A significant relationship was shown between the extent of leaf abnormalities and distance from human settlement (R2 = 0.0775, F(1, 703) = 59.05, p = 5.173e-14), with the extent of leaf abnormalities increasing as distance from human settlement increased. It was concluded that human settlement proximity within the Mgwashi ward of Tanzania does not directly influence tree health using visual indicators of ill health. Future research should utilize a larger sample size, incorporate objective indicators of ill tree health, and analyze environmental conditions within each plot to thoroughly analyze the impact of human settlement proximity on ill tree health.