2.5 Population abundance and density estimation
A free software program SPACECAP package version 3.0.2 (Gopalaswamy et al., 2012) was run to estimate snow leopard density from genetic samples; a user-friendly software package, implementing a Bayesian Spatially Explicit Capture Recapture (SECR) analysis (Royle et al., 2009). This software is recommended by Efford et al. (2009) for spatial CR data originating from different types of non-invasive sources, such as camera traps, hair snares or fecal DNA samples. SECR models in the SPACECAP package directly estimates animal density by explicitly using information on capture histories in combination with spatial locations of captures under a Bayesian modeling framework.
Following Singh et al. (2010), three types of input files were prepared to analyze data in the SPACECAP package: I. e. (i) Animal Capture Details, (ii) Trap Deployment Details and (iii) State-space Details. The trap deployment file consisted of trap location ID and spatial location of trap IDs in X and Y- coordinates (Universal Transverse Mercator UTM projection system) along with information on the occasions when each individual location was operational during the sample collection duration. Here the mid-center of grids was used as detectors (location) and we also reduced the number of sampling occasions by pooling the data together across three days due to a low encounter probability, as suggested by Janecka et al., 2011. The trap deployment data were organized in a two-dimensional matrix of individually identified locations and sampling occasions in a binary format (1s and 0s), indicating whether an individual location was or was not operational on a particular sampling occasion. A mesh of points (potential home range center) in each cell (0.25 km2) was generated using the Arc Geographical Information System (GIS) in a sampling array and 1.6 km buffer. The potential home range center file consisted of X and Y coordinates of all the potential activity centers in the UTM Projection System, and a habitat suitability indicator (using 1s or 0s) representing the potential activity centers within suitable or unsuitable habitat. The analysis was run in SPACECAP v 3.1 under the program R environment. For MCMC simulation, 60000 iterations were selected, 1000 burn in values (number of initial values to discard during the MCMC analysis) and 1 as thinning which was recommended by Royle et al. (2009). Only iteration numbers defined by the thinning rate are stored for the analysis (Singh et al., 2010). Since there was uncertainty about the total number of animals, which was likely to be larger than the minimum number identified during fecal DNA analysis, the value needed to be “augmented”. Here fecal DNA analysis identified 19 individual snow leopards in this survey, thus data augmentation has been set at 100 as a rule thumb this was 5 times greater (Royle et al., 2009).