Savannah and forest elephants in Uganda 191


FIG. 2 Illustrations of the six morphological criteria and their states (Table 1) used to distinguish between the two species, showing the typical phenotype of the savannah (a, d) and the forest elephant (c, e), and an example of an intermediate phenotype (b).


tracks. There were elephants in 1,408 of the 12,483 videos captured during November 2017–March 2018 by 14 camera traps (13 high-definition Reconyx XR-6 Ultrafire video traps, Reconyx, Holmen, USA; one high-definition Bushnell Trophy Cam HD Maxvideo trap, Bushnell, Overland Park, USA). In these videos, we analysed 1,215 oc- currences (i.e. observation of one individual elephant in a single video clip or observations of one individual in several consecutive videos). To study the global phenotypic variability by linking specimens and variables, we performed a multiple corre- spondence analysis (MCA; Abdi & Williams, 2010) using the mca function of the FactoMineR library (Lê et al., 2008). We conducted this analysis on the complete dataset (reference photographs and the Sebitoli sample), with no missing data. To visualize potential clusters, we performed a kernel density plot on the MCA using the kde function from the package ks (Charcón & Duong, 2018)in R (Supplementary Fig. 2; R Core Team, 2019). We made a species assignment key (Supplementary


Table 1) based on the six criteria previously validated in stage 1 of the survey, to facilitate the distinction between


forest and savannah elephants from direct and indirect ob- servations in the field. The criteria were divided into two categories (main criteria: C1,C2,C3; secondary criteria: C4,C5,C6) according to their visibility on the camera-trap footage; the secondary criteria were often barely visible. As elephants with intermediate phenotypes could also be seen in these forest savannah ecotones, we included the possibility of intermediate phenotypes in the species assignment key. We also noted when each criterion was not visible.We then used this key to determine the pheno- type of the individual. When possible we determined the sex and age class (infant, juvenile, subadult or adult) of the elephant. To validate our hypothesis that the two species and hy-


brids are present in the Sebitoli area, we cross-referenced our results from the species assignment key with results from the unsupervised K-means approach (Hartigan & Wrong, 1979) using the kmeans function in R. To partition phenotypic variability into K clusters, this algorithm mini- mizes the sum of the squares of the distances from a point to the average of the points of its cluster. As the K-means algorithm requires the number of groups to be defined, we


Oryx, 2023, 57(2), 188–195 © The Author(s), 2022. Published by Cambridge University Press on behalf of Fauna & Flora International doi:10.1017/S0030605321001605


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