CMSY模型参数敏感性分析:以西印度洋重要鱼类种群为例

Parameters sensitivity analysis of CMSY model: a case study of important fish populations in Western Indian Ocean

  • 摘要: 渔业资源可持续利用亟需有效的评估方法。传统评估方法因数据需求量大而受限,促使数据有限的评估方法迅速发展。其中,仅需捕捞数据的蒙特卡洛模拟捕捞量-最大可持续产量 (Monte Carlo Catch-MSY, CMSY) 模型应用广泛,但其参数设定可能影响结果可靠性。文章以西印度洋15 种主要经济鱼类种群为例,开展CMSY模型的参数敏感性分析,并评估其资源状况。结果表明,不同鱼类种群对模型参数 (Bend/k,相对生物量) 变化的响应存在差异,其中云鲥 (Tenualosa ilisha) 和剑鱼 (Xiphias gladius) 最为显著。除了龙头鱼 (Harpadon nehereus)、乳香鱼 (Lactarius lactarius) 和大眼金枪鱼 (Thunnus obesus) 外,大部分鱼类种群资源状况均处于捕捞型过度捕捞和资源型过度捕捞状态。与以往研究相比,中上层鱼类与中下层鱼类的CMSY模型结果基本一致;而金枪鱼类的评估结果则与印度洋金枪鱼委员会 (Indian Ocean Tuna Commission, IOTC) 基于数据充足方法的结论有较大差异。这表明CMSY模型在金枪鱼类资源评估中具有较高的不确定性,但对中上层小型鱼类和中下层鱼则表现出较好的适用性和可靠性。

     

    Abstract: The sustainable utilization of fishery resources urgently requires effective assessment methods. Traditional assessment approaches are constrained by their substantial data requirements, which has accelerated the development of data-limited evaluation methods. Among these, the Monte Carlo Catch-MSY (CMSY) model, which requires only catch data, has been widely applied. However, its parameter settings may significantly impact the results. Therefore, we selected 15 major economic fishpopulations in the Western Indian Ocean to analyze the parameter sensitivity of the CMSY model and assess their stock status. The results show that there were differences in the response of different fish populations to changes in model parameters (Bend/k), with hilsa shad (Tenualosa ilisha) and swordfish (Xiphias gladius) being the most significant. Except for bombay-duck (Harpadon nehereus), false trevally (Lactarius lactarius) and bigeye tuna (Thunnus obesus). All other fish stocks are considered to be both subject to overfishing and overfished. Compared with previous studies, the results of the CMSY model for pelagic fishes and other groundfishes are generally consistent, while for tuna, there are significant differences with the assessment results by Indian Ocean Tuna Commission (IOTC) by using data-rich methods. Therefore, the CMSY model performs poorly in the assessment of tuna but has good applicability and reliability in the application of small pelagic fishes and other groundfishes.

     

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