Our paper aims at advancing global change management in marine archipelago environments. Water properties vary along temporal and vertical gradients, and studies indicate that these patterns may be site-specific, i.e., they may vary at local or regional scales. Understanding these complex processes is crucial for designing environmental monitoring campaigns or assessing the scalability of their results. To our knowledge, the four-dimensional (temporal, vertical and horizontal) patterns of water quality have not been statistically quantified. In this paper, we partition the variation in four key water property variables into temporal, vertical and horizontal dimensions, by utilising a unique pre-existing high-density dataset and multilevel regression modelling. The dataset comprised measurements of temperature, salinity, pH and chlorophyll-a concentration, sampled eight times from April to October on the SW Finnish archipelago coast. All variables were sampled along the depth gradient and at local (10² m) and regional scales (10⁴ m) at 20 sites. All measured variables varied significantly along the temporal and vertical gradients, and the overall levels, temporal patterns and vertical gradients of these variables were significantly site-dependent. Our study confirms that many water properties, especially chlorophyll-a concentration, show high four-dimensional variability in the complex archipelago environment. Thus, studies on the regional dynamics of archipelago water properties call for a high sampling density in time, along the vertical gradient, and in space.

中文翻译：

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微咸群岛海岸水属性时空测量的可扩展性

我们的论文旨在推进海洋群岛环境中的全球变化管理。水属性随时间和垂直梯度而变化，研究表明这些模式可能是特定地点的，即它们可能在局部或区域尺度上有所不同。了解这些复杂的过程对于设计环境监测活动或评估其结果的可扩展性至关重要。据我们所知，水质的四维（时间、垂直和水平）模式尚未被统计量化。在本文中，我们通过利用独特的预先存在的高密度数据集和多级回归建模将四个关键水属性变量的变化划分为时间、垂直和水平维度。该数据集包括温度、盐度、pH 值和叶绿素-a 浓度，从 4 月到 10 月在芬兰西南群岛海岸采样了 8 次。所有变量沿深度梯度和局部（10² m) 和20 个站点的区域尺度 (10 ⁴ m)。所有测量变量沿时间和垂直梯度变化显着，并且这些变量的总体水平、时间模式和垂直梯度显着依赖于站点。我们的研究证实，在复杂的群岛环境中，许多水的特性，尤其是叶绿素-a 浓度，显示出高度的四维变异性。因此，对群岛水特性区域动态的研究需要在时间、垂直梯度和空间上进行高采样密度。