Data underlying the publication: Differences in bed elevation shape subtidal mussel bed stability under high-energy hydrodynamic events

In this study, we aimed to determine the stability of subtidal soft-bottom mussel beds under hydrodynamic disturbances through in-situ monitoring and to apply these insights to perform risk assessments in a typical region. Specifically, we hypothesized that the stability of these mussel beds is closely linked to changes in the motion of mussel clusters, which are expected to <em>i</em>) occur when specific hydrodynamic thresholds are exceeded and <em>ii</em>) exhibit noticeable spatial heterogeneity. To test this hypothesis, we developed retrievable Biophys loggers for the long-term, high-frequency monitoring of mussel cluster behavior under hydrodynamic disturbances. The Dutch Wadden Sea, inhabited by subtidal soft-bottom mussel beds, was employed as a model system, with eight sites selected for the deployment of Biophys loggers. The data were expected to facilitate quantification of the mobility threshold for each mussel bed and establish a relationship between inter-site variations in the mobility threshold and key environmental features. Furthermore, a statistical model was constructed to reproduce wave regimes over the past 11 years and calculate the return interval (i.e., average occurrence frequency) of the site-specific mobility threshold. Shorter return intervals of mobility thresholds at specific locations indicate lower stability in mussel beds and thus a higher risk of fragmentation or collapse during high-energy hydrodynamic events.These files include the data used to create each figure in the manuscript, organized as follows:<br>1. Concept diagram a) Fates of soft-bottom mussel beds: Figure 1 in the manuscript b) Spatial distribution of monitoring plots: Figure 2 in the manuscript c) Setup for in-situ monitoring: Figure 3 in the manuscript 2. Flume test a) Calibration results on accelerometers: Figure 4 in the manuscript 3. Field monitoring a) Data example from Biophy loggers: Figure 5 in the manuscript b) Multi-location threshold quantification: Figure 6 in the manuscript c) Relationships between the threshold and environmental variables: Figure 7 in the manuscript 4. Modeling a) Model outcome: Figure 8 in the manuscript b) Correlation between modeled data and real data: Figure 9 in the manuscript For a complete description, see “Data description.docx”