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剩余产量模型是最简单和应用最广泛的渔业资源评估模型之一。CEDA(catch-effort data analysis)和ASPIC(a surplus-production model incorporating covariates)是使用非平衡剩余产量模型对渔业产量和捕捞努力量数据进行分析的计算机软件。根据中国台湾延绳钓渔业的单位捕捞努力量渔获量(CPUE)数据,利用CDEA和ASPIC软件对南大西洋长鳍金枪鱼(Thunnus alalunga)渔业进行研究。结果显示,CEDA中使用对数正态误差假设的Fox模型产生了最大的R2值以及最接近ASPIC分析结果的种群参数值,但是CEDA得到的R2值低于ASPIC。CEDA对不同初始B1/K值的反应比ASPIC敏感。ASPIC中Logistic产量模型对不同初始B1/K值的反应比Fox模型更加灵敏。CEDA和ASPIC得出的最大可持续产量基本一致。
The residual yield model is one of the simplest and most widely used models for estimating fishery resources. CEDA (catch-effort data analysis) and ASPIC (a surplus-production model incorporating covariates) are computer software that analyzes data on fisheries production and fishing effort using unbalanced residual production models. Based on data on unit-harvested catch (CPUE) of longline fisheries in Taiwan, China, studies were conducted on the fisheries of the South Atlantic albacore Thunnus alalunga using CDEA and ASPIC software. The results showed that the Fox model using log-normal error assumption in CEDA produced the maximum R2 value and the population parameter value closest to the ASPIC analysis result, but the CEDA R2 value was lower than ASPIC. CEDA response to different initial B1 / K values is more sensitive than ASPIC. The Logistic production model in ASPIC responded more sensitively to different initial B1 / K values than the Fox model. CEDA and ASPIC reached the maximum sustainable yield basically the same.