Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Miller JR

PROVIDER: S-EPMC4377277 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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

Miller Jennifer R B JR Jhala Yadvendradev V YV Jena Jyotirmay J Schmitz Oswald J OJ

Ecology and evolution 20150302 6

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 ...[more]

PMID: 25859339

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Project description:Conservation conflict over livestock depredation is one of the key drivers of large mammalian carnivore declines worldwide. Mitigating this conflict requires strategies informed by reliable knowledge of factors influencing livestock depredation. Wild prey and livestock abundance are critical factors influencing the extent of livestock depredation. We compared whether the extent of livestock predation by snow leopards Panthera uncia differed in relation to densities of wild prey, livestock, and snow leopards at two sites in Shey Phoksundo National Park, Nepal. We used camera trap-based spatially explicit capture-recapture models to estimate snow leopard density; double-observer surveys to estimate the density of their main prey species, the blue sheep Pseudois nayaur; and interview-based household surveys to estimate livestock population and number of livestock killed by snow leopards. The proportion of livestock lost per household was seven times higher in Upper Dolpa, the site which had higher snow leopard density (2.51 snow leopards per 100 km2) and higher livestock density (17.21 livestock per km2) compared to Lower Dolpa (1.21 snow leopards per 100 km2; 4.5 livestock per km2). The wild prey density was similar across the two sites (1.81 and 1.57 animals per km2 in Upper and Lower Dolpa, respectively). Our results suggest that livestock depredation level may largely be determined by the abundances of the snow leopards and livestock and predation levels on livestock can vary even at similar levels of wild prey density. In large parts of the snow leopard range, livestock production is indispensable to local livelihoods and livestock population is expected to increase to meet the demand of cashmere. Hence, we recommend that any efforts to increase livestock populations or conservation initiatives aimed at recovering or increasing snow leopard population be accompanied by better herding practices (e.g., predator-proof corrals) to protect livestock from snow leopard.

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Project description:Limited information exists on mercury concentrations and environmental drivers of mercury bioaccumulation in high latitude terrestrial carnivores. Spatial patterns of mercury concentrations in wolverine (Gulo gulo, n = 419) were assessed across a 1,600,000 km2 study area in relation to landscape, climate, diet and biological factors in Arctic and boreal biomes of western Canada. Hydrogen stable isotope ratios were measured in wolverine hair from a subset of 80 animals to assess the spatial scale for characterizing environmental conditions of their habitat. Habitat characteristics were determined using GIS methods and raster datasets at two scales, the collection location point and a 150 km radius buffer, which was selected based on results of a correlation analysis between hydrogen stable isotopes in precipitation and wolverine hair. Total mercury concentrations in wolverine muscle ranged >2 orders of magnitude from 0.01 to 5.72 μg/g dry weight and varied geographically, with the highest concentrations in the Northwest Territories followed by Nunavut and Yukon. Regression models at both spatial scales indicated diet (based on nitrogen stable isotope ratios) was the strongest explanatory variable of mercury concentrations in wolverine, with smaller though statistically significant contributions from landscape variables (soil organic carbon, percent cover of wet area, percent cover of perennial snow-ice) and distance to the Arctic Ocean coast. The carbon and nitrogen stable isotope ratios of wolverine muscle suggested greater mercury bioaccumulation could be associated with feeding on marine biota in coastal habitats. Landscape variables identified in the modelling may reflect habitat conditions which support enhanced methylmercury transfer to terrestrial biota. Spatially-explicit estimates of wet atmospheric deposition were positively correlated with wolverine mercury concentrations but this variable was not selected in the final regression models. These landscape patterns provide a basis for further research on underlying processes enhancing methylmercury uptake in high latitude terrestrial food webs.

Dataset Information

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

Publications

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

Similar Datasets

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