Distance sampling and spatial capture-recapture for estimating density of Northern Bobwhite

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Obtaining accurate density estimates is critical for managers making decisions regarding wildlife populations. A variety of methods have been used to estimate population density, with two of the most common being distance sampling (DS) and spatial capture recapture (SCR). We evaluated precision and bias of density estimators through a simulation study of DS using data collected from either human observer point counts or automated recording units (ARUs), and SCR using trapping data or trapping data augmented with telemetry data. We then fit each of the four models to empirical data collected during autumn 2016–2018 for a population of northern bobwhite Colinus virginianus on Di-Lane Wildlife Management Area in Georgia. Density estimates in our simulation study were relatively unbiased using all four methods but were most accurate for the two SCR methods. Empirical density estimates were similar across methods and years, with annual averages of 0.41 birds per ha in 2016, 0.44 birds per ha in 2017 and 0.31 birds per ha in 2018. In general, both SCR methods were also the most precise using the empirical data, although ARU distance sampling did also produce comparable density estimates and precision values. Although SCR methods performed the best overall, cost and increased labor of these monitoring programs should be evaluated in relation to the relative ease of ARU deployment or point count surveys, which also provided adequate, and often similar, density estimates. Integrating these constraints into a structured decision-making framework will aid managers weighing decisions regarding how to monitor, and ultimately make management decisions.