Spatial variability in subtidal hard substrate assemblages across horizontal and vertical gradients: a multi-scale approach using seafloor imaging
Knowledge of spatial patterns in subtidal hard substrate assemblages is necessary for the development of effective marine management strategies. However, patterns are intrinsically scale-dependent, and little is known about the relative importance of vertical and horizontal position changes across s...
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Veröffentlicht in: | Marine ecology. Progress series (Halstenbek) 2020-01, Vol.633, p.23-36 |
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Sprache: | eng |
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Zusammenfassung: | Knowledge of spatial patterns in subtidal hard substrate assemblages is necessary for the development of effective marine management strategies. However, patterns are intrinsically scale-dependent, and little is known about the relative importance of vertical and horizontal position changes across scales. In the southwestern Baltic Sea, major physicochemical attributes (e.g. salinity, temperature, nutrients) change sharply across different spatial scales. We tested the hypothesis that biological variation generally increases with increasing scales and that horizontal (along-shore) variability becomes at least comparable in magnitude to vertical variation at large scales. An imaging approach was chosen to span a distance of 200 km within which 3 scales (small: a few km; meso: 10s of km; large: 100s of km) along the vertical and horizontal axes were examined and compared. In total, 1800 images were analyzed for species composition and cover. Most biological variability was detected across the large scale, along the horizontal salinity gradient. Species richness decreased with decreasing salinity, and assemblage composition changed significantly. At the meso scale, vertical variation along the bathymetric gradient (10−40 m) appeared to be the dominant pattern. The least variation occurred at the small scale. Vertical zonation and small-scale variation were stronger at higher salinities. The study highlighted horizontal gradients as potential drivers for spatial variability in this system. The multi-scale approach used here was particularly useful for detecting the interactive effects between scales and gaining insights applicable to large-scale management. |
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ISSN: | 0171-8630 1616-1599 |
DOI: | 10.3354/meps13168 |