Uncertainty hampers innovative mixed‐fisheries management by the scales at which connectivity dynamics are relevant to management objectives. The spatial scale of sustainable stock management is species‐specific and depends on ecology, life history and population connectivity. One valuable approach to understand these spatial scales is to determine to what extent population genetic structure correlates with the oceanographic environment. Here, we compare the level of genetic connectivity in three codistributed and commercially exploited demersal flatfish species living in the North East Atlantic Ocean. Population genetic structure was analysed based on 14, 14 and 10 neutral DNA microsatellite markers for turbot, brill and sole, respectively. We then used redundancy analysis (RDA) to attribute the genetic variation to spatial (geographical location), temporal (sampling year) and oceanographic (water column characteristics) components. The genetic structure of turbot was composed of three clusters and correlated with variation in the depth of the pycnocline, in addition to spatial factors. The genetic structure of brill was homogenous, but correlated with average annual stratification and spatial factors. In sole, the genetic structure was composed of three clusters, but was only linked to a temporal factor. We explored whether the management of data poor commercial fisheries, such as in brill and turbot, might benefit from population‐specific information. We conclude that the management of fish stocks has to consider species‐specific genetic structures and may benefit from the documentation of the genetic seascape and life‐history traits.

中文翻译：

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协调三种共生比目鱼的海景遗传学和渔业科学

不确定性会影响连接动态与管理目标相关的尺度，从而影响创新的混合渔业管理。可持续种群管理的空间规模因物种而异，取决于生态，生活史和人口连通性。了解这些空间尺度的一种有价值的方法是确定种群遗传结构与海洋环境之间的相关程度。在这里，我们比较了生活在东北大西洋的三种共同分布和商业开发的深海比目鱼物种的遗传连通性水平。分别基于14种，14种和10种中性DNA微卫星标记分别分析了大菱,、 bri和唯一的种群遗传结构。然后，我们使用冗余分析（RDA）将遗传变异归因于空间（地理位置），时间（采样年）和海洋（水柱特征）组成部分。菱turbo的遗传结构除空间因素外，还由三个簇组成，并且与比考克林深度的变化有关。毛的遗传结构是同质的，但与年平均分层和空间因素相关。单独地，遗传结构由三个簇组成，但是仅与时间因素相关。我们探讨了对数据贫乏的商业性渔业（如麻花鱼和大比目鱼）的管理是否可能受益于特定人群的信息。