Shortfin mako sharks, Isurus oxyrinchus, were listed under Appendix II of CITES in 2019 in part due to the results of the last stock assessment for the North Atlantic population, which determined the population is overfished and experiencing overfishing. With population numbers expected to continue to decline, the managing body, the International Commission for the Conservation of Atlantic Tunas (ICCAT), has called for efforts to reduce shortfin mako bycatch. We evaluate the potential for reducing mako bycatch by identifying mako hot sets, those with particularly high shortfin mako bycatch. Environmental conditions were evaluated for their influence on catch per unit effort (CPUE) of shortfin mako sharks. Standardized CPUEs were calculated from the US pelagic longline observer program (2004–2012) using a generalized additive model (GAM) with a delta-lognormal approach applied to the environmental variables sea surface height, sea surface temperature, bathymetry, and chlorophyll-a concentration. Quantile regression (QR) was also performed to evaluate whether environmental variables can predict fishing conditions with high CPUE. The results of the GAM and QR methods were compared and assessed for their ability to predict and identify locations where shortfin mako CPUE is particularly high. The results suggest that using the binomial portion of the delta-lognormal model, the probability of positive bycatch, is the best basis to define an algorithm to avoid setting in conditions that might have high mako bycatch. Bycatch avoidance strategies built from probability of positive bycatch perform well enough at identifying hot sets to avoid half the shortfin mako bycatch with only a 20% reduction in effort.

短鳍鲭鲨，Isurus oxyrinchus，在 2019 年被列入 CITES 附录 II，部分原因是北大西洋种群的最后一次种群评估结果，该结果确定种群被过度捕捞并正在经历过度捕捞。由于种群数量预计将继续下降，管理机构国际大西洋金枪鱼保护委员会 (ICCAT) 呼吁努力减少短鳍鲭鱼兼捕。我们通过识别 mako 热集来评估减少 mako 兼捕的潜力，那些短鳍 mako 兼捕量特别高。评估了环境条件对短鳍鲭鲨单位努力捕获量 (CPUE) 的影响。标准化 CPUE 是根据美国远洋延绳钓观察员计划（2004-2012 年）使用广义加性模型 (GAM) 计算得出的，该模型对环境变量海面高度、海面温度、水深测量和叶绿素-a 浓度采用 delta 对数正态方法. 还进行了分位数回归 (QR) 以评估环境变量是否可以预测具有高 CPUE 的捕鱼条件。对 GAM 和 QR 方法的结果进行了比较和评估，以确定它们预测和识别短鳍鲭鱼 CPUE 特别高的位置的能力。结果表明，使用 delta-lognormal 模型的二项式部分，即正副渔获物的概率，是定义算法的最佳基础，以避免设置可能具有高 mako 副渔获物的条件。