Morphological variation of the kelp Ecklonia cava along the Korean coast in relation to local environmental conditions

Version 2 — adds raw environmental data, derived environmental descriptors, analysis code, and documentation to the original morphological dataset. This dataset and analysis code accompany the manuscript: Choi, D.M., Han, J., Ko, Y.W., Yang, K.M. & Kim, J.H. Morphological variation of the kelp Ecklonia cava along the Korean coast in relation to local environmental conditions. Overview The deposit provides the raw individual-level morphological measurements, the raw long-term environmental records, a derived site-level environmental table, and the Python code needed to reproduce the statistical analyses and main figures (Fig. 4–6) of the study. Morphology of 397 Ecklonia cava thalli was measured at 11 sites along the southern and eastern coasts of Korea, including Jeju Island (sampled May–July 2012), and analysed against six long-term (2008–2012) environmental descriptors derived from the Korean Marine Environment Information System (MEIS). Files Morphology trait_with ratios.xlsx — Raw individual-level morphology: 397 individuals × 10 traits (total length, stipe length, stipe diameter, lamina length, lamina width, number of laterals, lateral length, lateral width, holdfast wet weight, total thallus wet weight) plus two derived ratios (holdfast wet-weight ratio, stipe length ratio). Environment(2008-2012).xlsx — Raw monthly MEIS observations (198 records) for temperature, salinity, turbidity, transparency, dissolved inorganic nitrogen (DIN) and phosphorus (DIP). environmental_site_descriptors.csv — Derived site-level table: per-site multi-year mean ± SE and sample size (n) for the six variables, with coordinates, depth range, habitat description, a light-environment axis, and a flag for the single interpolated cell (GEO transparency). 01_meis_preprocessing.py — Builds the site-level environmental table from the raw MEIS file; documents the GEO transparency interpolation and the light-environment axis (PC1 of turbidity and transparency). 02_analysis_figures.py — Reproduces the SIMPER analysis, the site-level correlation matrix with FDR control (Fig. 4), the individual-level linear mixed-effects models (Fig. 5 / Table 4), VIF screening, and the parsimonious redundancy analysis (Fig. 6). README.md — Full variable definitions, units, missing-value handling, run instructions and software versions. LICENSE — CC-BY-4.0 licence text. Reproducibility Analyses run under Python 3.12 (NumPy, SciPy, pandas, statsmodels, scikit-learn, matplotlib, openpyxl). Running 01_meis_preprocessing.py followed by 02_analysis_figures.py regenerates the environmental descriptor table, the statistical tables, and Figures 4–6. Aggregating the raw MEIS records reproduces the published site-level environmental means and per-cell sample sizes. Full details are in README.md. Notes The environmental records originate from the Korean Marine Environment Information System (MEIS; https://www.meis.go.kr) and are provided here as processed for this study. Transparency at the Geomundo (GEO) site was not recorded in the archive and is the only interpolated value, reconstructed from the across-site log–log transparency–turbidity relationship and flagged in the data.