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”

本研究旨在通过原位监测（in-situ monitoring），明确潮下带软底贻贝床在水动力扰动（hydrodynamic disturbances）下的稳定性，并将所得研究结论应用于典型区域的风险评估工作。具体而言，本研究提出假设：此类贻贝床的稳定性与贻贝群的运动变化密切相关，且该运动变化预计将满足两个特征：(i) 当特定水动力阈值（hydrodynamic thresholds）被突破时发生；(ii) 呈现显著的空间异质性（spatial heterogeneity）。为验证该假设，本研究研发了可回收式Biophys记录仪（Biophys loggers），用于对水动力扰动下的贻贝群行为开展长期、高频监测。本研究以分布有潮下带软底贻贝床的荷兰瓦登海（Dutch Wadden Sea）作为模式系统，并选取8个站点部署Biophys记录仪。本研究预期所得数据可用于量化各贻贝床的运动阈值，并阐明运动阈值的站点间差异与关键环境特征之间的关联。此外，本研究构建了统计模型，以重现过去11年间的波浪工况，并计算各站点专属运动阈值的重现间隔（即平均发生频率）。特定站点的运动阈值重现间隔越短，则对应贻贝床的稳定性越低，在高能水动力事件（high-energy hydrodynamic events）中发生破碎或坍塌的风险也就越高。本数据集包含论文中所有图表对应的原始数据，具体组织形式如下：
1. 概念图示
a) 软底贻贝床的归宿：论文图1
b) 监测样地的空间分布：论文图2
c) 原位监测装置布设方案：论文图3
2. 水槽试验
a) 加速度计校准结果：论文图4
3. 野外监测
a) Biophys记录仪的示例数据：论文图5
b) 多站点阈值量化结果：论文图6
c) 阈值与环境变量间的关联：论文图7
4. 模型构建
a) 模型输出结果：论文图8
b) 模拟数据与实测数据的相关性：论文图9
如需完整说明，请参阅"Data description.docx"