Part 4: GPS Telemetry Detection Rates (GPS Test Collar Sites), GCS NAD 83 (2015)

Bias correction in GPS telemetry data-sets requires a strong understanding of the mechanisms that result in missing data. We tested wildlife GPS collars in a variety of environmental conditions to derive a predictive model of fix acquisition. We found terrain exposure and tall over-story vegetation are the primary environmental features that affect GPS performance. Model evaluation showed a strong correlation (0.924) between observed and predicted fix success rates (FSR) and showed little bias in predictions. The model's predictive ability was evaluated using two independent data-sets from stationary test collars of different make/model, fix interval programming, and placed at different study sites. No statistically significant differences (95% CI) between predicted and observed FSRs, suggest changes in technological factors have minor influence on the models ability to predict FSR in new study areas in the southwestern US.GPS（全球定位系统，Global Positioning System）遥测数据集的偏置校正，需要充分理解导致数据缺失的内在作用机制。本研究在多种环境条件下对野生动物GPS项圈开展测试，以构建定位信号获取率的预测模型。研究发现，地形暴露度与高大上层植被是影响GPS性能的核心环境因素。模型评估结果显示，观测得到的定位成功率（Fix Success Rate，FSR）与模型预测值之间存在极强相关性（相关系数为0.924），且预测结果仅存在极小偏置。本研究采用两组独立数据集对模型的预测能力进行验证：这两组数据集分别来自不同品牌/型号、不同定位间隔编程方案的固定式测试项圈，且部署于不同研究区域。经检验，预测与观测得到的FSR之间未出现统计学意义上的显著差异（95%置信区间，95% CI），这表明技术参数的变化对模型在美国西南部新研究区域预测FSR的能力仅存在微弱影响。