Distance estimation error data and code "Bias in density estimates from avian point-count surveys: prospects for post-hoc corrections using calibration data"

We collected field data where we had observers estimate distances to singing birds and other field staff confirm the singing locations of the same birds to examine relationships between estimated versus measured distances. Our objectives were to 1) estimate the magnitude of bias in density estimates for distance sampling models in the presence of distance estimation error, and 2) use separate field data to examine whether post-hoc corrections of EDRs can reduce bias in estimated densities. We apply our post-hoc corrections to simulations and empirical point-count data collected in the boreal forest of Saskatchewan, Manitoba and Northwest Territories, Canada to demonstrate the magnitude of change in density estimates we expect in real-world data..本研究采集了野外实测数据集：由观测员对鸣禽与自身的距离进行估算，同时由其他野外工作人员确认同一只鸣禽的鸣唱位置，以此探究估算距离与实测距离之间的关联。本研究的核心目标有二：其一，量化存在距离估算误差时，距离采样模型（distance sampling models）的密度估算结果的偏差幅度；其二，利用独立的野外数据集，探究估计探测距离（EDRs）的事后校正是否能够降低密度估算的偏差。我们将所提出的事后校正方法应用于加拿大萨斯喀彻温省、曼尼托巴省以及西北地区的北方针叶林（boreal forest）中采集的模拟数据与实测点计数（point-count）数据，以此展示真实世界数据中密度估算结果的预期变化幅度。