渔业数据失真对两种非平衡剩余产量模型评估结果的影响比较

为了研究渔业数据失真对两种非平衡剩余产量模型评估结果的影响,以南大西洋长鳍金枪鱼渔业产量和单位捕捞努力量渔获量(CPUE)数据作为基础数据,加入5种不同程度[变异系数(CV)=1%、5%、10%、20%和30%]的随机误差,模拟了(1)无数据失真,(2)仅产量数据失真,(3)仅CPUE数据失真,(4)产量和CPUE数据均失真等4种情况。利用基于ASPIC的非平衡剩余产量模型(ASM)和基于贝叶斯状态空间建模方法的非平衡剩余产量模型(BSM)分别评估了最大可持续产量(MSY)、B_(MSY)、F_(MSY)、B_(2011)/B_(MSY)、F2011/F_(MSY)等5种生物学参考点和管理指标。结果显示,在无数据失真情况下,ASM和BSM评估的MSY分别为2.866×10~4 t和2.836×10~4 t,B_(2011)/B_(MSY)分别为1.366和1.324,F2011/F_(MSY)分别为0.627和0.667,均相差不大,表明该渔业目前状态良好,ASM得到了较大的B_(MSY)(31.48×10~4 t)和较小的F_(MSY)(0.091);数据失真对ASM评估的B_(MSY)和F_(MSY)分别产生了严重的过低估计和过高估计,且CPUE数据失真产生的影响要比产量数据失真大;随着随机误差的增大,BSM评估的生物学参考点和管理指标的绝对百分比偏差有增大趋势;与ASM相比,BSM能够更好地处理渔业数据中存在的随机误差,除了MSY以外,BSM评估的生物学参考点和管理指标绝对百分比偏差均要比ASM的评估结果低,尤其是B_(MSY)和F_(MSY)。因此,在使用存在较大随机误差的渔业数据进行资源评估时,BSM具有一定的优势。     

Predicting use of habitat patches by spawning horseshoe crabs (Limulus polyphemus) along a complex coastline with field surveys and geospatial analyses

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