Illinois Natural History Survey, University of Illinois, Champaign, Illinois, United States of America.
Wisconsin Department of Natural Resources, Rhinelander, Wisconsin, United States of America.
PLoS One. 2020 May 21;15(5):e0233444. doi: 10.1371/journal.pone.0233444. eCollection 2020.
Catch-per-unit-effort (CPUE) is often used to monitor wildlife populations and to develop statistical population models. Animals caught and released are often not included in CPUE metrics and their inclusion may create more accurate indices of abundance. We used 21 years of detailed harvest records for bobcat (Lynx rufus) in Wisconsin, U.S.A., to calculate CPUE and 'actual CPUE' (ACPUE; including animals caught and released) from bobcat hunters and trappers. We calibrated these metrics to an independent estimate of bobcat abundance and attempted to create simple but effective models to estimate CPUE and ACPUE using harvest success data (i.e., bobcats harvested/available permits). CPUE showed virtually no relationship with bobcat abundance across all years, but both CPUE and ACPUE had stronger, non-linear, and negative relationships with abundance during the periods when the population was decreasing. Annual harvest success strongly predicted composite ACPUE and CPUE from hunters and trappers and hunter ACPUE and CPUE but was a poorer predictor of trapper ACPUE and CPUE. The non-linear, and sometimes weak, relationships with bobcat abundance likely reflect the increasing selectivity of bobcat hunters for trophy animals. Studies calibrating per-unit-effort metrics against abundance should account for population trajectories and different harvest methods (e.g., hunting and trapping). Our results also highlight the potential for estimating per-unit-effort metrics from relatively simple and inexpensive data sources and we encourage additional research into the use of per-unit-effort metrics for population estimation.
渔获努力量（CPUE）常用于监测野生动物种群并开发统计种群模型。被捕获并放生的动物通常不包括在 CPUE 指标中，而包括这些动物可能会创建更准确的丰度指数。我们使用美国威斯康星州 21 年的详细猎捕记录，计算了来自猎人和诱捕者的山猫（Lynx rufus）的 CPUE 和“实际 CPUE”（包括捕获和释放的动物）。我们将这些指标与山猫丰度的独立估计值进行校准，并试图使用猎捕成功数据（即已捕获的山猫/可用许可证）创建简单但有效的模型来估计 CPUE 和 ACPUE。CPUE 几乎与所有年份的山猫丰度都没有关系，但 CPUE 和 ACPUE 与丰度之间的关系更强，呈非线性和负相关，特别是在种群减少的时期。年度猎捕成功率强烈预测了猎人/诱捕者的综合 ACPUE 和 CPUE 以及猎人的 ACPUE 和 CPUE，但对诱捕者的 ACPUE 和 CPUE 的预测能力较差。与山猫丰度的非线性和有时较弱的关系可能反映了山猫猎人对奖杯动物的选择性越来越强。校准 CPUE 等单位努力量指标与丰度的研究应该考虑到种群轨迹和不同的猎捕方法（例如，狩猎和诱捕）。我们的结果还突出了从相对简单和廉价的数据源估计单位努力量指标的潜力，我们鼓励对使用单位努力量指标进行种群估计进行更多研究。
