Research On Amur Tiger(Panthera Tigris Altaica) Individual Identification From Snow Footprints

Effective monitoring of the existing Amur tiger (Panthera tigris altaica) populations is the foundation of various management and recovery measures. And the core job of effective monitoring is to identify Amur tiger individuals accurately. However, because of its extremely small population size and low density, any sample collected in the field is valuable, the estimate standard of Russia could not meet the needs of Amur tiger monitoring. During the winter from Nov.2011to Mar.2012, we collected snow footprint imags from44known captive Amur tiger, which were born from1999to2009and had ages from3to13years old. At each age, there were2males and2females. We used the customized script in JMP10.0software to extract data from the images, and used the data to build the model for individual and sex identification.1. For sex identification, a total of523footprint images from87trails of40known captive Amur tigers (19females and21males) were used to explore a better method to indentify their sex by their footprint images(female mean age=8.07±0.18, male mean age=8.36±0.19, F=1.18, P>0.05). We used a linear discriminant analysis in JMP software (SAS institute) to determine sex. With10variables selected, we got a track accuracy of97.9%. Dividing the60%data into a training set and40%into a test set for prediction, we got the accuracy of97.5%.2. For individual identification, we selected a total of479footprint images from69trails of32known captive Amur tigers (17females and15males) to build the model. Using a customized script in JMP software based on the robust cross-validated discriminant analysis in conjunction with a Ward’s clustering method, the system gave an estimate of31animals (actually from32individuals) for the captive population, giving97%accuracy. Dividing the50%data into a training set and50%into a test set, the predicted classification of the trails in the cluster analysis also gave a result that these footprints were from17individuals (actually from16). The accuracy is93.75%.3. Based on these results, snow footprints can be used for sex and individual identification of Amur tiger. This technology is a potential valuable tool for a wild Amur tiger monitoring in large scale landscape scale.