The productivity of intertidal shellfish banks is affected by a wide variety of environmental parameters. In this study, a battery of multivariate analyses including generalized linear mixed models, hierarchical cluster analysis and principal component analysis were performed to define the spatial organization of sandbanks and to identify the variables driving the grouping. Grain‐size distribution and calcium carbonate, organic matter, Si and Al oxides, and trace metals content were the variables used to characterize the intertidal sediments. Field data were collected through the upper 50 cm in 57 sites located in shellfish sandbanks from five coastal inlets of the western Cantabrian coast (Rías Altas, north‐west Iberian Peninsula). Generalized linear mixed models showed that hardly any variable differed with core depth, and the hierarchical cluster analysis and principal component analysis revealed that the banks organized around four clusters. This grouping was dictated by the influence of the imprint of the Cabo Ortegal complex material (with high levels of MgO, Mn, Cr, Ni, V and Fe₂O₃) or by the imprint of the Ollo de Sapo and Manto de Mondoñedo (high levels of SiO₂, Rb, K₂O and Ba). The multivariate analysis also separated the sandbanks with higher terrestrial influence in the inner part of the inlets (high levels of Al₂O₃, Zn, Ba and TiO₂) from those with higher marine influence, which were located in the outer part (high levels of Sr, CaO and CaCO₃). Furthermore, it was observed that both axes of main ordination were related to the annual average concentration of chlorophyll‐a and inorganic nitrogen in the water column above those sediments, highlighting the interdependence between chemical composition of the overlying water and sediments’ characteristics. This approach, combining parametric models and multivariate analyses of textural and geochemical sediment composition data, proved to be useful for characterizing intertidal substrates where shellfish species live.

中文翻译：

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多变量底物表征：RíasAltas（西北伊比利亚半岛）贝类收获区的情况

潮间带贝类库的生产力受到多种环境参数的影响。在这项研究中，进行了一系列多元分析，包括广义线性混合模型，层次聚类分析和主成分分析，以定义沙丘的空间组织并确定驱动分组的变量。粒度分布和碳酸钙，有机质，硅和铝氧化物以及痕量金属含量是用来表征潮间带沉积物的变量。现场数据是从坎塔布连西部西部五个沿海入口（伊比利亚半岛西北部的里亚斯·阿塔斯）的贝类沙洲的57个站点的上方50厘米处收集的。广义线性混合模型表明，随芯深的变化几乎没有任何变化，层次聚类分析和主成分分析表明，银行围绕四个聚类组织。这种分组是由Cabo Ortegal复合材料（具有高含量的MgO，Mn，Cr，Ni，V和Fe的烙印）的影响所决定的。₂ O ₃）或Ollo de Sapo和Manto deMondoñedo（高含量SiO ₂，Rb，K ₂ O和Ba）的印记。多变量分析还将入口内部（Al ₂ O ₃，Zn，Ba和TiO ₂含量高）的陆地影响较高的沙洲与外部（高）影响较大的沙洲分开。Sr，CaO和CaCO _3的水平）。此外，还观察到主序的两个轴都与叶绿素a的年平均浓度有关。沉积物上方水柱中的无机氮，突出了上覆水的化学成分与沉积物特征之间的相互关系。这种方法结合了参数模型和纹理和地球化学沉积物成分数据的多变量分析，被证明对表征贝类生活的潮间带基质很有用。