Background/Question/Methods - Photographic mark-recapture is a cost-effective, non-invasive way to study populations. However, to effectively apply photographic mark-recapture to large populations, computer software is needed for efficient image manipulation and pattern matching. This talk describes a new software package and its application to giraffe (Giraffa camelopardalis) populations in the Tarangire Ecosystem in northern Tanzania.

Results/Conclusions - We created an open source application for the storage, pattern extraction, and pattern-matching of digital images for the purposes of mark-recapture analysis. The resulting software package is a stand-alone, multi-platform application implemented in Java. Over 1200 images were acquired in the field in three primary sampling periods, Sept.-Oct. 2008, Jan.-Mar. 2009, and Dec. 2009.  The pattern information in these images was extracted and matched resulting in capture histories for over 600 unique individuals.  These histories were then analyzed with Cormack-Jolly-Seber models to estimate survival rates and closed population models to estimate population sizes for two spatially distinct subpopulations.  Our program employs the SIFT operator (Scale Invariant Feature Transform) which extracts distinctive features invariant to image scale and rotation. This was advantageous in this application as it allowed reduced preprocessing of images and accepted a greater range of image quality with low matching error rates.  This new tool allowed photographic mark-recapture to be applied successfully to this relatively large population and suggests it can be successfully applied to other suitable species.