Station-level intertidal macrofauna data and analysis code from an eco-engineered seawall in the Jitimen Waterway, China (2024–2025)
Description
This dataset supports the manuscript “Rapid taxonomic turnover during early assembly of intertidal macrofauna on an eco-engineered seawall in a subtropical estuary”. It contains quantitative intertidal macrofauna data collected from the artificial-rock habitat of the East Levee along the Jitimen Waterway, Zhuhai, China. Sixteen fixed stations were distributed among four shore-normal transects (D1–D4), with one high-shore, two mid-shore, and one low-shore station per transect. Surveys were conducted in September 2024, March 2025, and May 2025, approximately 2, 8, and 10 months after construction completion. At each station, two 0.0625 m² quadrats were pooled to form a quantitative sampling area of 0.125 m². The dataset comprises 48 station-survey observations, 748 individuals, and 32 accepted taxa. The deposited files include cleaned station metadata, taxonomically standardized count and wet-biomass matrices, a taxonomic crosswalk linking reported and accepted scientific names, derived ecological variables, statistical outputs, and the Python code used for the analyses. The reproducible workflow covers univariate repeated-station permutation tests, community composition analyses, NMDS, PERMANOVA, PERMDISP, and the partitioning of temporal Jaccard dissimilarity into turnover and nestedness-resultant components. The dataset contains no pre-construction observations or independent reference-shoreline data. It is therefore intended for reproducing the reported temporal comparisons within the constructed shoreline and should not be interpreted as providing a causal estimate of restoration effectiveness.
Files
Steps to reproduce
Download and extract the reproducibility archive while retaining its original directory structure. Create a Python 3.12 environment and install pandas 2.2.3, NumPy 2.3.5, SciPy 1.17.0, scikit-learn 1.8.0, matplotlib, seaborn, and Pillow. Open a terminal in the reproducibility/scripts directory. Run python run_all.py to reproduce the univariate permutation tests, PERMANOVA, temporal beta-diversity partitioning, taxon-level contrasts, NMDS, and PERMDISP analyses. Run python make_manuscript_figures.py to regenerate Figures 1–4. Reproduced tables and statistical outputs are written to the reproducibility/results directory, and regenerated figures are written to reproducibility/figures_generated. Additional information on the analytical sequence, taxonomy, and interpretation boundaries is provided in reproducibility/README.md.