Predictive mapping of tree species assemblages in an African montane rainforest

Study design To account for the different environmental conditions, we employed a stratified random sampling approach. The park was divided into five strata based on geological formations visible on the Digital Elevation Model (DEM) of Bwindi and the starting points on the boundary of the DEM in each stratum were selected randomly with the random point function within ArcGIS (version 10.5; ESRI, Redlands, CA, USA). Line transects were drawn on the DEM in each stratum from the random starting points to traverse the topographic positions of the ridges (Figure 1; Table 1). The number and length of the transects selected varied with area, accessibility and shape of the strata. We then superimposed the transect drawings on high-resolution (0.5m) true color, digital aerial photographs of Bwindi. The aerial photos were visually interpreted along the transects by drawing polygons around areas perceived to be of uniform tree community structure based on differences in tone and texture. This allowed the sample sites to be placed in what we perceived to be distinct tree communities. Tree species sampling We carried a printed copy of the digitized polygons, overlaid with a coordinate grid, and used a hand-held Global Positioning System (GPS) device to locate the digitized polygons in the field. A single random point within each digitized polygon was selected for tree species sampling. At each random sample point, we used the point-to-tree distance technique or plotless sampling method to sample trees (Hall, 1991; Sheil et al., 2003; Klein & Vilcko, 2006). This technique involved selecting the nearest 15 trees (≥20 cm dbh) around the random center-point. The selected trees were identified to species level and we measured the diameter at breast height (dbh) of each individual. We named the tree species following nomenclature used in Kalema and Hamilton (2020). The distance from the sample site center-point to the 15th farthest tree was measured and regarded as the sample site radius. This procedure is suitable for rapid and robust assessments of vegetation where tree density varies, such as in patchy and disturbed tropical forest (Sheil et al., 2003; Klein & Vilcko, 2006). At each center-point, eight environmental attributes were recorded: aspect – as the compass direction facing down slope; and steepness of the slope using a clinometer. Untransformed aspect and slope are poor for quantitative analysis, so slope was transformed to a more suitable index by taking the sine of the slope in degrees; aspect was also transformed into a suitable index by taking the negative cosine of the angle in degrees minus 35 (McCune & Grace, 2002). Four physiographic positions of valley, hillside, ridge tops and gully were simply recorded as “1” if the sample site was in that physiographical class and “0” otherwise. The final recorded site characteristics consisted of spatial variables – the Universal Transverse Mercator (UTM) coordinates of easting and northing (datum WGS 84) using a hand-held GPS unit, standardized to zero mean and unit variance. All the data were collected at 289 sample sites spread across the forest (Figure 1).