Fisheries Resource and Analysis Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 2725 Montlake Boulevard East, Seattle, Washington 98112, USA.
Ecol Appl. 2013 Oct;23(7):1645-58. doi: 10.1890/12-2225.1.
Fisheries bycatch is driven by both ecological (e.g., area, season) and social (e.g., fisher behavior) factors that are often difficult to disentangle. We demonstrate a method for comparing fishery-dependent bycatch to fishery-independent catch to delineate the influence of ecological and social factors on bycatch and provide insights for bycatch management. We used data from commercial fishing vessels in the U.S. west coast trawl groundfish fishery (fishery-dependent data collected by fisheries observers) and scientific data from the U.S. west coast bottom trawl groundfish survey (fishery-independent data) to compare the relative effects of season, time of day, target group, depth, and latitude on the expected catch of 12 bycatch species of management interest. This comparison highlights two important relationships that help identify drivers of bycatch. First, when the effect of season, time of day, depth, or latitude on bycatch in both the commercial and scientific data is positive, ecological processes are likely strong drivers of bycatch, suggesting technical approaches (e.g., temporal or spatial closures, gear modifications) might effectively control bycatch. Alternatively, when the effects of season, time of day, depth, latitude, or target group appear only in the commercial data (but not in survey data), fisher behavior is likely the stronger driver of bycatch, suggesting a need to strengthen incentives for fishers to change behavior to avoid bycatch (e.g., regulatory quotas). Two other patterns emerge that suggest that fishery bycatch is not associated with temporal, target, or spatial variables, implying that either current incentives to avoid bycatch are working (i.e., when survey expected catch is positively correlated with variables, but fishery catch is not) or bycatch is a product of unstudied or stochastic processes (i.e., variables are not correlated with expected catch in either data set) and continued monitoring is recommended. Our analysis provides managers and fishers with a basic analytical framework to assess bycatch reduction alternatives and methods useful for researchers interested in comparing bycatch before and after a management shift.
渔业副渔获物是由生态（如面积、季节）和社会（如渔民行为）因素共同驱动的，而这些因素往往难以区分。我们展示了一种将渔业依赖型副渔获物与渔业独立型渔获物进行比较的方法，以确定生态和社会因素对副渔获物的影响，并为副渔获物管理提供见解。我们使用了美国西海岸拖网底层鱼类渔业中的商业渔船数据（由渔业观察员收集的渔业依赖型数据）和美国西海岸底层鱼类拖网调查数据（渔业独立型数据），比较了季节、一天中的时间、目标群体、深度和纬度对 12 种管理感兴趣的副渔获物物种的预期渔获量的相对影响。这种比较突出了两个重要的关系，有助于确定副渔获物的驱动因素。首先，当季节、一天中的时间、深度或纬度对商业和科学数据中副渔获物的影响为正时，生态过程很可能是副渔获物的主要驱动因素，这表明技术方法（如时间或空间关闭、渔具修改）可能有效地控制副渔获物。相反，当季节、一天中的时间、深度、纬度或目标群体的影响仅出现在商业数据中（而不在调查数据中）时，渔民行为很可能是副渔获物的更强驱动因素，这表明需要加强对渔民改变行为以避免副渔获物的激励措施（例如监管配额）。还有另外两种模式表明，渔业副渔获物与时间、目标或空间变量无关，这意味着当前避免副渔获物的激励措施正在发挥作用（即当调查预期渔获量与变量呈正相关时，但渔业渔获量没有），或者副渔获物是未研究或随机过程的产物（即变量与两个数据集的预期渔获量都不相关），建议继续监测。我们的分析为管理者和渔民提供了一个基本的分析框架，以评估减少副渔获物的替代方案和方法，也为有兴趣在管理转变前后比较副渔获物的研究人员提供了有用的方法。
