For the first time ever, tiger numbers in the Russian Far East were estimated using remote cameras set in the forest to “capture” tigers automatically on film. Because the stripes of each tiger are unique, it is possible to differentiate and count tigers based on photographic evidence. Camera-trapping studies conducted in Sikhote-Alin Biosphere Zapovednik (SABZ) from 2006 to 2008 provided the basis for providing the most statistically robust estimates of tiger densities ever derived for the Amur tiger.
Despite the fact that camera-traps have been used successfully over many years to monitor tiger densities in India, where this method was first developed, there was no certainty that this method would be successful with Amur tigers, which occur at much lower densities, and are therefore much more difficult to photograph. For this reason, one of our major goals was to determine the efficacy of using camera traps to estimate numbers of tigers that naturally occur at very low densities.
Sikhote-Alin Biosphere Reserve (SABZ) is the largest protected area within the Amur tiger’s distribution range, making it a useful “laboratory” to conduct our studies.Because of its size and the variety of habitats it encompasses, we divided the reserve into three study areas, which coincide with specific habitat types. In the coastal zone near the Sea of Japan, oak forests are the predominate forest type. Further inland, but on the coastal side of the Sikhote-Alin Mountains, Korean pine-mixed deciduous forests (historically the predominant habitat type across tiger range in Russia) are dominant. On the inland side of the Sikhote-Alin Mountains, more boreal conditions exist in the Kolumbe river Basin, where spruce-fir forests are most common.
Obtaining useful statistically reliable estimates of tiger numbers is dependent on high “capture” rates (large numbers of photos) of tigers. Because our team knows much of the study area so thoroughly (from years of study) and knows how to search for tiger sign and where to place cameras, capture rates were high. We obtained 378 photos of 24 individual tigers across the entire reserve: 10 females, 9 males and 5 individuals of undetermined sex were photographed. Twenty of the 24 tigers were photographed more than once and 5 tigers were regularly registered by camera-traps over all 3 years of research. Highest tiger densities were observed in Oak and Korean pine-deciduous forests, (both about 0.8 individuals per 100 km2) with lower densities (0.1 individuals per 100 km2) reported in the fir-spruce forest zone.
Nearly all other estimates of tiger numbers in Russia are based on expert estimates of tiger numbers derived from recording information on track sizes and distribution in winter snows. While this approach has great appeal (it is relatively inexpensive, and the method is well accepted in Russia), there is no way to determine the precision or error based on the traditional track survey method, and therefore difficult to define how accurate this approach is. Most importantly, track surveys may not provide sufficient precision to identify downturns in the tiger population. Camera trapping, on the other hand, is well grounded and statistically robust, allowing the possibility to accurately monitor trends in tiger numbers.
Further studies will help determine the relationship of track surveys and camera-trap surveys, but for now, we are considering new survey approaches that would combine camera trapping in core areas combined with wider track counts. Such a combined approach may reconcile the needs for precise estimates, and the need to cover vast areas of the Russian Far East. In the end, we are looking for the most accurate, cost-efficient method to count tigers in the remote reaches of the Russian Far East.