Poaching of wildlife presents one of the biggest conservation challenges in the 21st century. Snaring is one of the primary means of capturing target animals. To prioritise interventions intending to reduce snaring, we describe an approach for quantifying the configuration and lethality of snares. We conducted transect surveys in Murchison Falls National Park. All the snares that we recovered were made of wire with the majority (81.0%, n = 546 of 674) deriving from vehicle tire wire. The density of snares ranged from 0.08 to 4.58 snares/km2, which is the highest known density in sub‐Saharan Africa. The majority (63%) of the animals caught in wire snares were unrecovered and wasted. We found that noose width, vertical drop, wire circumference, anchor height, proportion of un‐thicketed area, grass height, distance to river and village had a significant positive relationships to lethality, while snare thickness, charms, tree DBH, thicket diameter, distance to nearest road negatively affected lethality. We recommend adopting wholistic anti‐snare countermeasures such as the human heritage‐centred conservation to empower local people. Our method illustrates the opportunity to standardise temporal and spatial measurements of snare density and configuration necessary to stop illegal wildlife poaching.

Quantifying the distribution and size of home ranges is critical for understanding animal spatial dynamics. This is particularly important for large carnivores in fragmented landscapes. Most studies that estimate home range consider only a bivariate frequency distribution represented by a two‐dimensional planimetric surface. The underlying assumption of these approaches is that the animals inhabit landscapes that are completely flat. Of course, this is rarely the case. Here we investigated the influence of vertical relief and three‐dimensional landscape features on the home range patterns of a high density carnivore. Via GPS telemetry‐tracking of a population of Persian leopards Panthera pardus saxicolor (n = 6), and globally‐available digital elevation models (DEMs), we calculated the surface area of home ranges in comparison to traditional planimetric estimates. We also investigated predation patterns of leopards across elevation gradients using GPS location data and kill site analysis. The topographic measurements exceeded planimetric estimates by up to 38% which suggests that planimetric modeling underestimates home range size, particularly when animals inhabit variable terrain. We also observed that resident leopards exhibit significant altitudinal partitioning of predation, suggesting that leopards that have overlapping home ranges may still utilize exclusive hunting territories. We discuss the ways in which planimetric approaches may be underestimating aspects of animal ranging behavior and ecology. We conclude that topography should be considered, not as an ancillary metric, but as an important aspect of home range calculation. Our approach can enhance understanding of spatial requirements, population density, intra‐guild sympatric competition and conflict management of large felids inhabiting rugged landscapes.

Home ranges provide a conceptual and quantitative representation of animal-habitat associations over time. Methods to estimate home ranges have swiftly progressed by dynamically accounting for various sources of bias. Across that period of growth, one potentially influential source of bias has yet to be robustly scrutinized. Animals inhabiting the terrestrial spatial domain make movement decisions in environments with variable landscape complexity.Despite that reality, home range estimation methods tend to be informed by two-dimensional (2D) data (i.e., X and Y coordinates) which analytically presume that these landscapes are flat. This analytical tendency potentially misrepresents the configuration and size of animal home range estimates. To examine the prevalence of this bias, we reviewed literature of terrestrial animal home range estimation published between 2000 and 2019. We recorded the proportion of studies that; i) recognized and ii) incorporated landscape complexity. Over 22.0% (n = 271) of the 1,203 studies recognized the importance of landscape complexity for animal movement. Interestingly, just 0.7% (n = 8) incorporated landscape complexity into the home range estimation. We infer then that landscape complexity represents an important source of bias resulting in the underestimation of terrestrial animal home range size. Given the influence of landscape complexity on terrestrial animal decision-making, energetics, and fitness our analysis highlights an important gap in current home range methodologies. We discuss the implications of our analysis for biased understandings of terrestrial animal spatial ecology with subsequent impacts on management and conservation practices built upon these estimates.

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