Camera trapping photographic rate as an index of density in forest ungulates

Summary 1. Calibrating indices of animal abundance to true densities is critical in wildlife studies especially when direct density estimations are precluded by high costs, lack of required data or model parameters, elusiveness and rarity of target species. For studies deploying camera traps, the use of photographic rate (photographs per sampling time) as an index of abundance potentially applies to the majority of terrestrial mammals where individual recognition, and hence capture–recapture analysis, are unfeasible. The very few studies addressing this method have either been limited by lack of independence between trapping rates and density estimations, or because they combined different species, thus introducing potential bias in camera trap detection rates. This study uses a single model species from several sites to analyse calibration of trapping rates to independently derived estimations of density. The study also makes the first field test of the method by Rowcliffe et al. (2008) for density derivation from camera trapping rates based on modelling animal‐camera contacts. 2. We deployed camera traps along line transects at six sites in the Udzungwa Mountains of Tanzania and correlated trapping rates of Harvey’s duiker Cephalophus harveyi with densities estimated from counts made along the same transects. 3. We found a strong, linear relationship ( R 2 = 0·90) between trapping rate and density. Sampling precision analysis indicates that camera trapping rates reach satisfactory precision when trapping effort amounts to 250–300 camera days. Density estimates using Rowcliffe et al. ’s (2008) gas model conversion are higher than from transect censuses; we discuss the possible reasons and stress the need for more field tests. 4. Synthesis and applications . Subject to rigorous and periodic calibration, and standardization of sampling procedures in time and over different sites, camera trapping rate is shown to be, in this study, a valid index of density in the target species. Comparative data indicate that this may also apply to forest ungulates in general. The method has great potential for standardizing monitoring programmes and reducing the costs of wildlife surveys, especially in remote areas.