Evaluation of camera trapping as a method for estimating raccoon (Procyon lotor) and opossum (Didelphis virginiana) densities
Camera traps are widely used in wildlife surveys, oftentimes to estimate the abundance of animals with uniquely identifiable markings, such as big cats. Methods to estimate animal density without the need for individual recognition have been developed which are based upon the idea that trapping rate can be applied as an index of abundance. With such methods, camera traps have the potential to become a valuable tool in conservation research; however, density estimation from camera trap data remains controversial. This research tests the model developed by Rowcliffe et al. (2008) by comparing density estimates from camera trap data to estimates obtained from mark-recapture studies of raccoons and opossums. Camera trap surveys were conducted at eight different sites across the central and eastern United States from 2010 to 2012. Throughout this same period, animals were censused using live traps spaced along grids located within three replicate arrays per site. Population estimates for raccoons and opossums at all eight sites were obtained using a robust design model in program MARK. Camera trapping rates, as defined by Rovero et al. (2009) were correlated with densities estimated from mark-recapture data to determine whether trapping rate is a valid index of animal density.
Successful application of camera trapping to density estimation would greatly extend the value of camera trap data beyond its current uses by allowing scientists to estimate animal density when capture-recapture studies are unfeasible. However, in this study, linear regression analysis demonstrated no correlation between camera trapping rate and abundance. Despite previous studies supporting the potential of camera trapping rate as an index of abundance, camera trapping rate in this study is not shown to be a valid index of density in raccoons and opossums. Based on these results, we suggest that, while camera trapping may be an effective technique for obtaining presence/absence data, camera data alone is not enough to estimate population density.