In 2017, a new regulatory management system, the traffic light system (TLS), was implemented to estimate the effects of salmon lice from Norwegian salmon aquaculture on marine survival of wild Atlantic salmon and forms the basis of aquaculture capacity regulation. The TLS relies on observational data and a set of models to estimate the risk for negative impact on wild salmon populations. This review of the literature that forms the basis for the TLS as well as other relevant studies is presented in the context of the currently practiced TLS and suggestions are made for immediate and long‐term improvements. The main findings of this review are that: (1) assumed timing and duration of smolt migration contribute to unreliable observational and modelled data and overestimates of infection pressure; (2) production of lice larvae from farmed salmon is overestimated; (3) TLS model systems rely on or are calibrated by the same potentially flawed data; (4) lice‐associated mortality in wild salmon smolts may be overestimated; and (5) lice infection levels on farms are not associated with measurable effects on wild salmon. Recommendations to improve the accuracy and reliability of the TLS, and hence its environmental efficiency include the more complete use of available biological and physical environmental variables, adjusting the time period that observational data are registered and modelled data are integrated, adjusting the interpretation of data including recognition of uncertainty in model outcomes, and use of more realistic assumptions concerning lice‐induced mortality thresholds.

中文翻译：

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鲑鱼虱子生物学、环境因素和小鲑鱼行为对挪威鲑鱼养殖管理系统的影响：批判性评论


2017年，实施了新的监管管理系统——红绿灯系统（TLS），以评估挪威鲑鱼养殖中的鲑鱼虱子对野生大西洋鲑鱼海洋生存的影响，并构成水产养殖能力监管的基础。 TLS 依靠观测数据和一组模型来估计对野生鲑鱼种群产生负面影响的风险。对构成 TLS 基础的文献以及其他相关研究的回顾是在当前实践的 TLS 的背景下提出的，并提出了立即和长期改进的建议。本次综述的主要发现是：（1）假设的小鲑鱼迁徙时间和持续时间导致了不可靠的观察和建模数据以及对感染压力的高估； (2) 养殖鲑鱼的虱子幼虫产量被高估； (3) TLS模型系统依赖于相同的潜在缺陷数据或通过相同的潜在缺陷数据进行校准； (4) 野生鲑鱼幼鱼与虱子相关的死亡率可能被高估； (5) 养殖场的虱子感染水平与对野生鲑鱼的可测量影响无关。提高 TLS 的准确性和可靠性及其环境效率的建议包括更完整地利用现有的生物和物理环境变量、调整观测数据注册和建模数据整合的时间段、调整数据解释，包括认识到模型结果的不确定性，并使用关于虱子引起的死亡率阈值的更现实的假设。