The salmonid fish Brown trout is iconic as a model for the application of conservation genetics to understand and manage local interspecific variation. However, there is still scant information about relationships between local and large‐scale population structure, and to what extent geographical and environmental variables are associated with barriers to gene flow. We used information from 3,782 mapped SNPs developed for the present study and conducted outlier tests and gene–environment association (GEA) analyses in order to examine drivers of population structure. Analyses comprised >2,600 fish from 72 riverine populations spanning a central part of the species' distribution in northern Europe. We report hitherto unidentified genetic breaks in population structure, indicating strong barriers to gene flow. GEA loci were widely spread across genomic regions and showed correlations with climatic, abiotic and geographical parameters. In some cases, individual loci showed consistent GEA across the geographical regions Britain, Europe and Scandinavia. In other cases, correlations were observed only within a sub‐set of regions, suggesting that locus‐specific variation was associated with local processes. A paired‐population sampling design allowed us to evaluate sampling effects on detection of outlier loci and GEA. Two widely applied methods for outlier detection (pcadapt and bayescan) showed low overlap in loci identified as statistical outliers across sub‐sets of data. Two GEA analytical approaches (LFMM and RDA) showed good correspondence concerning loci associated with specific variables, but LFMM identified five times more statistically significant associations than RDA. Our results emphasize the importance of carefully considering the statistical methods applied for the hypotheses being tested in outlier analysis. Sampling design may have lower impact on results if the objective is to identify GEA loci and their population distribution. Our study provides new insights into trout populations, and results have direct management implications in serving as a tool for identification of conservation units.

中文翻译：

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北欧鲑鱼 (L.) 种群在不同地理区域和环境梯度上存在遗传差异。


鲑鱼褐鳟鱼是应用保护遗传学来理解和管理当地种间变异的标志性模型。然而，关于当地和大规模人口结构之间的关系，以及地理和环境变量在多大程度上与基因流动障碍相关的信息仍然很少。我们使用了为本研究开发的 3,782 个映射的 SNP 的信息，并进行了异常值测试和基因-环境关联 (GEA) 分析，以检查人口结构的驱动因素。分析包括来自 72 个河流种群的 >2,600 条鱼，这些种群跨越北欧物种分布的中心部分。我们报告了迄今为止尚未发现的种群结构遗传断裂，这表明基因流动存在强大的障碍。 GEA 基因座广泛分布在基因组区域，并显示出与气候、非生物和地理参数的相关性。在某些情况下，各个基因座在英国、欧洲和斯堪的纳维亚半岛的地理区域中表现出一致的 GEA。在其他情况下，仅在区域子集中观察到相关性，这表明位点特异性变异与局部过程相关。配对群体抽样设计使我们能够评估抽样对异常基因座和 GEA 检测的影响。两种广泛应用的异常值检测方法（ pcadapt和bayescan ）显示，在数据子集中被识别为统计异常值的位点重叠度较低。两种 GEA 分析方法（LFMM 和 RDA）在与特定变量相关的基因座方面表现出良好的对应性，但 LFMM 发现的统计显着关联性比 RDA 高出五倍。 我们的结果强调了仔细考虑用于异常值分析中测试的假设的统计方法的重要性。如果目标是确定 GEA 基因座及其群体分布，则抽样设计对结果的影响可能较小。我们的研究提供了对鳟鱼种群的新见解，其结果对于作为识别保护单位的工具具有直接的管理意义。