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.,… Click to show full abstract
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.
               
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