Ecosystems & Environment Research Centre, School of Environment & Life Sciences, Peel Building, The Crescent, University of Salford, Greater Manchester, M5 4WT, UK.
Sci Rep. 2017 Oct 9;7(1):12852. doi: 10.1038/s41598-017-12301-x.
Illegal, unreported and unregulated (IUU) fishing and seafood supply chain fraud are multifaceted problems that demand multifaceted solutions. Here, we investigate the extent to which global fisheries trade data analyses can support effective seafood traceability and promote sustainable seafood markets using one of the world's most highly prized, yet misunderstood, groups of fishes as a model: the snappers, family Lutjanidae. By collating and comparing production, import and export data from international and national statistical collections for the period 2006-2013, we show that official trade data severely lack the level of detail required to track snapper trade flows, uncover potential IUU activities and/or inform exploitation management of snappers and related species. Moreover, we contend that the lack of taxonomic granularity and use of vague generic names in trade records represent one of the most insidious impediments to seafood traceability, and suggest that widely used harmonised commodity classification systems should evolve to address these gaps.
非法、未报告和无管制（IUU）捕捞和海鲜供应链欺诈是多方面的问题，需要多方面的解决方案。在这里，我们研究了全球渔业贸易数据分析在多大程度上可以支持有效的海鲜可追溯性，并利用世界上最受重视但最被误解的鱼类之一——鲷科鱼类作为模型来促进可持续的海鲜市场。通过整理和比较 2006-2013 年期间国际和国家统计数据集中的生产、进口和出口数据，我们表明，官方贸易数据严重缺乏跟踪鲷鱼贸易流量、发现潜在 IUU 活动和/或为鲷鱼和相关物种的捕捞管理提供信息所需的详细程度。此外，我们认为，在贸易记录中缺乏分类学上的细微差别和使用模糊的通用名称是海鲜可追溯性的最阴险障碍之一，并建议广泛使用的商品协调分类系统应发展以解决这些差距。
