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首页> 外文期刊>ICES Journal of Marine Science >Managing a complex population structure: exploring the importance of information from fisheries-independent sources
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Managing a complex population structure: exploring the importance of information from fisheries-independent sources

机译：管理复杂的人口结构：探索独立于渔业的信息来源的重要性

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Natural resource managers aim to manage fish stocks at sustainable levels. Often, management of these stocks is based on the results of analytical stock assessments. Accurate catch data, which can be attributed to a specific population unit and reflects the population structure, are needed for these approaches. Often though, the quality of the catch data is compromised when dealing with a complex population structure where fish of different population units mix in a fishery. The herring population units west of the British Isles are prone to mixing. Here, the inability to perfectly allocate the fish caught to the population unit they originate from, due to classification problems, poses problems for management. These mixing proportions are often unknown; therefore, we use simulation modelling combined with management strategy evaluation to evaluate the role fisheries-independent surveys can play in an assessment to provide unbiased results, irrespective of population unit mixing and classification success. We show that failure to account for mixing is one of the major drivers of biased estimates of population abundance, affecting biomass reference points and MSY targets. When mixing of population units occurs, the role a survey can play to provide unbiased assessment results is limited. Either different assessment models should be employed or stock status should be considered from the survey data alone. In addition, correctly classifying the origin of fish is especially important for those population units that are markedly smaller in size than other units in the population complex. Without high classification success rates, smaller population units are extremely vulnerable to overexploitation.
机译：自然资源管理者的目标是在可持续水平上管理鱼类资源。通常，这些库存的管理是基于分析库存评估的结果。这些方法需要可归因于特定种群单位并反映种群结构的准确捕捞数据。但是，当处理复杂的种群结构时，渔民数据的质量通常会受到影响，在这种结构中，不同种群单位的鱼混在一起从事渔业。不列颠群岛以西的鲱鱼种群容易混合。在这里，由于分类问题，无法将捕获的鱼完美地分配给它们所来自的种群单位，这给管理带来了麻烦。这些混合比例通常是未知的。因此，我们将模拟模型与管理策略评估相结合，以评估独立于渔业的调查在评估中可以发挥的作用，从而提供公正的结果，而与种群单位混合和分类成功无关。我们表明，无法考虑混合是人口数量偏差估计的主要驱动力之一，影响了生物量参考点和MSY目标。当人口单位混合发生时，调查在提供公正的评估结果中所扮演的角色是有限的。应该采用不同的评估模型，或者仅从调查数据中考虑库存状态。此外，对于鱼类种群的大小明显小于种群群中其他种群的种群，正确分类鱼类的来源尤其重要。没有较高的分类成功率，较小的人口单位极易遭受过度开发。

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