Recovery planning towards doubling wild tiger Panthera tigris numbers: Detailing 18 recovery sites from across the range.

With less than 3200 wild tigers in 2010, the heads of 13 tiger-range countries committed to doubling the global population of wild tigers by 2022. This goal represents the highest level of ambition and commitment required to turn the tide for tigers in the wild. Yet, ensuring efficient and targeted implementation of conservation actions alongside systematic monitoring of progress towards this goal requires that we set site-specific recovery targets and timelines that are ecologically realistic. In this study, we assess the recovery potential of 18 sites identified under WWF's Tigers Alive Initiative. We delineated recovery systems comprising a source, recovery site, and support region, which need to be managed synergistically to meet these targets. By using the best available data on tiger and prey numbers, and adapting existing species recovery frameworks, we show that these sites, which currently support 165 (118-277) tigers, have the potential to harbour 585 (454-739) individuals. This would constitute a 15% increase in the global population and represent over a three-fold increase within these specific sites, on an average. However, it may not be realistic to achieve this target by 2022, since tiger recovery in 15 of these 18 sites is contingent on the initial recovery of prey populations, which is a slow process. We conclude that while sustained conservation efforts can yield significant recoveries, it is critical that we commit our resources to achieving the biologically realistic targets for these sites even if the timelines are extended.

Landscape-scale accessibility of livestock to tigers: implications of spatial grain for modeling predation risk to mitigate human-carnivore conflict.

Innovative conservation tools are greatly needed to reduce livelihood losses and wildlife declines resulting from human-carnivore conflict. Spatial risk modeling is an emerging method for assessing the spatial patterns of predator-prey interactions, with applications for mitigating carnivore attacks on livestock. Large carnivores that ambush prey attack and kill over small areas, requiring models at fine spatial grains to predict livestock depredation hot spots. To detect the best resolution for predicting where carnivores access livestock, we examined the spatial attributes associated with livestock killed by tigers in Kanha Tiger Reserve, India, using risk models generated at 20, 100, and 200-m spatial grains. We analyzed land-use, human presence, and vegetation structure variables at 138 kill sites and 439 random sites to identify key landscape attributes where livestock were vulnerable to tigers. Land-use and human presence variables contributed strongly to predation risk models, with most variables showing high relative importance (≥0.85) at all spatial grains. The risk of a tiger killing livestock increased near dense forests and near the boundary of the park core zone where human presence is restricted. Risk was nonlinearly related to human infrastructure and open vegetation, with the greatest risk occurring 1.2 km from roads, 1.1 km from villages, and 8.0 km from scrubland. Kill sites were characterized by denser, patchier, and more complex vegetation with lower visibility than random sites. Risk maps revealed high-risk hot spots inside of the core zone boundary and in several patches in the human-dominated buffer zone. Validation against known kills revealed predictive accuracy for only the 20 m model, the resolution best representing the kill stage of hunting for large carnivores that ambush prey, like the tiger. Results demonstrate that risk models developed at fine spatial grains can offer accurate guidance on landscape attributes livestock should avoid to minimize human-carnivore conflict.