Knowledge of population size and spatial distribution is important for protection of threatened or endangered species, and management of harvested animal populations. Estimates of species’ abundance or density are useful as a baseline for developing protected areas, prioritizing conservation actions, and allocating harvest quotas. However, large mammals often persist at low densities over large areas, are not uniformly distributed, and have large home ranges. These characteristics may undermine abundance estimation and hinder subsequent conservation efforts. Capture-recapture methods are often used to estimate density and abundance of rare or elusive carnivores. Remote collection of DNA samples enables researchers to sample wide geographic areas, and has become Masitinib almost universal for bear capture-recapture studies. Nonetheless, trap configurations that do not adequately reflect population distributions and individual variation in space use may limit precise and accurate estimates of density and abundance. The spatial nature of sampling designs and wildlife populations are important components of estimating animal abundance. Non-spatial capture-recapture models often require study designs to cover several times the area of an individual home range, while maintaining trap spacing narrow enough to ensure individuals have nonzero and homogenous capture probabilities. However, for species with large home ranges and individual movements, logistical constraints may require a tradeoff between extensive coverage of a study area with wide trap spacing or intensive coverage of a portion of the study area with close spacing. Spatial capture-recapture models explicitly include animal movement and trap distribution, and therefore reduces constraints placed on sampling wide ranging species over large areas. Moreover, SCR defines a spatial point process model to estimate the home range centers of individuals detected, eliminating the need for ad hoc estimates of the effective sampling area. Therefore, SCR models address a primary source of heterogeneity inherent in most carnivore populations by addressing unequal exposure to traps and edge effects. Simulations of SCR parameter estimates from black bear trapping configurations were unbiased when movement was at least half the distance between traps and when trap coverage was similar to the extent of movement. Although SCR models are robust to unequal trap exposure and appear flexible to various spatial trapping designs, few studies have empirically tested the efficacy of SCR models using different largescale trap array configurations. The large home ranges of bears and constraints to large-scale sampling often preclude adequate coverage of individual space use. We tested a spatially extensive and intensive trapping scenario to compare how trap coverage and spacing affects precision of SCR parameter estimates using black bear DNA encounter history data from hair snare arrays.