Estimate of sustainable yield of blue shark ( Prionace glauca ) in the Indian Ocean using data-poor approach

Abstract

PDF HTML阅读 XML下载 导出引用 引用提醒 运用数据缺乏方法估算印度洋大青鲨可持续渔获量 DOI: 作者: 作者单位: 1. 上海海洋大学 海洋科学学院, 上海 201306;2. 农业部大洋渔业开发重点实验室, 上海 201306 作者简介: 耿喆(1993-),男,硕士研究生,从事渔业资源评估、渔业生态学研究.E-mail:gengzhe1993@sohu.com 通讯作者: 中图分类号: S931 基金项目: 国家自然科学基金项目（41676120）. Estimate of sustainable yield of blue shark (Prionace glauca) in the Indian Ocean using data-poor approach Author: Affiliation: 1. College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;2. Key Laboratory of Exploitation of Oceanic Fisheries, Ministry of Agriculture, Shanghai 201306, China Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:运用数据缺乏方法，即基于资源衰减的可持续渔获量估算模型（DCAC），结合Monte Carol模拟，对印度洋大青鲨（增大或最大可持续产量对应的捕捞死亡系数（）增大；若呈减小趋势。资源丰度指数的选择对DCAC结果有较大影响，基于日本延绳钓渔业1998-2014年和2001-2014年两个时间序列的丰度指数得到的结果可靠，且与其他模型估算的MSY值接近。2014年印度洋大青鲨的年渔获量正好处在或略高于最大可持续产量（MSY）水平，但该结果仍具有一定的不确定性。本研究表明运用DCAC方法估算印度洋大青鲨可持续渔获量是可行的，但对其他鲨鱼种类的适用性仍需进一步研究，该结果可为数据缺乏方法在大洋和中国近海渔业中的应用提供参考。 Abstract:Sharks occupy the top trophic level in the marine community and play an important role in maintaining ecosystem stability and diversity. The stock status of shark species is often difficult to assess by formal stock assessment methods due to limited fishery data. Blue shark () is the most widely distributed pelagic shark species in tropical and temperate oceanic waters. This species is often caught as bycatch in oceanic longline fisheries that target billfishes and tunas, and also in the artisanal longline fisheries that operate in coastal areas such as Chile. Because of its slow growth and late maturity, the blue shark is defined as "Near Threatened" globally in the IUCN species list. Determining the stock status of Indian Ocean blue shark using a data-poor approach has been assigned as a high research priority by the Indian Ocean Tuna Commission. In this study, we assessed the Indian Ocean blue shark stock status using the depletion-corrected average catch (DCAC) approach and Monte Carlo simulation. DCAC is a data-poor approach that only needs basic biological information (natural mortality, was estimated by the Hoeing method, resulting in a mean of 0.05. In addition to the annual catch data, the application of DCAC also needs the means and standard errors of the following parameters:depletion of the biomass (. First, we estimated the sustainable yield () of blue shark using abundance indices (standardized catch per unit effort[CPUE] time series) derived from different longline fleets (i.e., Spain, Portugal, Japan, and Taiwan, China). Second, we evaluated the sensitivity of DCAC by considering multiple combinations of different levels of , CPUE indices, and lengths of time series of data. Lastly, we summarized the estimated values and compared our estimates with the results from other assessment approaches for this species. The results showed that when FMSY/M when was close to zero or negative. The results were sensitive to the CPUE index. The estimated was reliable and close to the maximum sustainable yield (estimated from other assessment models) when the Japanese longline CPUE index (1998-2014 or 2001-2014) was used. The current (2014) annual catch of blue shark might be at or just above the estimated maximum sustainable yield, although the estimate is subject to uncertainties. This study suggests that DCAC is suitable for estimating the of Indian Ocean blue shark using catch data and CPUE indices as the main sources. This study also provides guidelines for the application of data-poor approaches in domestic fisheries of China. 参考文献 相似文献 引证文献