Caleb King, Research Statistician Tester, JMP
Jody Tucker, Deputy Program Manager and Biological Scientist, U. S. Forest Service
Ryan Lekivetz, Manager, Advanced Analytics R&D, JMP
Zoë Jewell, WildTrack Co-Founder, WildTrack
Sky Alibhai, WildTrack Co-Founder, WildTrack
The federally endangered southern Sierra Nevada fisher (Pekania pennanti) is spread out at low density across a large and rugged landscape, comprised of approximately 300 individuals across a 12,000 km2 area. Its vulnerability has been further amplified by periods of severe drought and extensive wildfires in the region.
Identifying and preserving female reproductive habitat has been outlined as the most important demographic feature for sustaining and increasing the population. In this presentation we describe a customized, cost-effective and non-invasive Footprint Identification Technique (FIT) in JMP software developed by WildTrack to identify both species and sex using footprints collected at track stations.
We created a data set of known fisher and Pacific marten (Martes caurina) footprint images and known-sex fisher images. To automate the feature extraction in JMP, we developed a customized script to generate distances, angles, and areas using landmark points on the footprint images. Using a single variable, we had a species classification accuracy of over 99%. For fisher sex classification, using a more parsimonious model with just two variables selected in LDA, we achieved accuracies of 94.0% for the training set and 89.4% for the test set. We discuss the merits of this technique to help with the conservation efforts for this species.
