Virtual plaster cast : digital 3D modelling of lion paws and tracks using close-range photogrammetry

The ecological monitoring of threatened species is vital for their survival as it provides the baselines for conservation, research and management strategies. Wildlife studies using tracks are controversial mainly due to unreliable recording techniques limited to two-dimensions (2D). We assess close-range photogrammetry as a lowcost, rapid, practical and reliable field technique for the digital three-dimensional (3D) modelling of lion Panthera leo paws and tracks. First, we tested three reconstruction parameters affecting the 3D model quality. We then compared direct measurements on the paws and tracks versus the same measurements on their digital 3D models. Finally, we assessed the minimum number of photographs required for the 3D reconstruction. Masking, auto-calibration and optimization provided higher reconstruction quality. Paws masked semi-automatically and tracks masked manually were characterized by a geometric deviation of 0.23 0.18 cm and 0.50 0.33 cm respectively. Unmasked tracks delineated by means of the contour lines had a geometric deviation of 0.06 0.39 cm. The use of a correction factor reduced the geometric deviation to 0.03 0.20 cm (pad-masked paws), 0.04 0.35 cm (pad-masked tracks) and 0.01 0.39 cm (unmasked tracks). Based on the predicted error, the minimum number of photographs required for an accurate reconstruction is seven (paws) or eight (tracks) photographs. This field technique, using only a digital camera and a ruler, takes less than one minute to sample a paw or track. The introduction of the 3D facet provides more realistic replications of paws and tracks that will enable a better understanding of their intrinsic properties and variation due to external factors. This advanced recording technique will permit a refinement of the current methods aiming at identifying species, age, sex and individual from tracks.National Research Foundation (NRF).http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1469-79982017-02-28hb2016Mammal Research InstituteZoology and Entomolog

Identification of the anteroposterior and mediolateral position of lion paws and tracks using 3D geometric morphometrics

Estimating the distribution and status of animal populations is crucial in various fields of biology. Monitoring species via their tracks is controversial due to unreliable recording techniques, manipulator bias and substrate variation. Furthermore, subjective identification of the foot that produces each track can lead to significant errors, for example, when assigning tracks made by different feet from the same individual to different individuals. The aim of this research was to develop an accurate, consistent and objective algorithm to identify the anteroposterior (hind/front) and mediolateral (right/left) position from digital threedimensional (3D) models of African lion (Panthera leo) paws and tracks using geometric morphometrics. We manually positioned 12 fixed landmarks on 132 paws and 182 tracks recorded in 3D using digital close-range photogrammetry. We used geometric morphometrics to evaluate and visualize the shape variation between paws and between tracks along the anteroposterior and mediolateral axes, and between paws and tracks. The identification algorithm using linear discriminant analysis with jack-knifed predictions reached a maximum accuracy of 95.45% and 91.21% for paws and tracks, respectively.We recommend the use of this objective position identification algorithm in future studies where tracks are compared between individual African lions