Mechanism‐based clustering reveals distinct controls on phytoplankton community composition across Korean marginal seas from integrated in situ and satellite observations ( KORUS ‐ OC 2016)

Phytoplankton regulate the marine food web, biogeochemical processes, and climate‐relevant carbon export to depth in the oceans, but the mechanisms controlling their distributions vary across space and time, limiting inference from pooled analyses. We developed a mechanism‐based clustering framework that groups stations by covariate–community response fingerprints inferred from a multivariate generalized linear mixed model (GLMM). Station‐specific random effects across major taxa were treated as fingerprints and clustered to define mechanism‐consistent groups; Geostationary Ocean Color Imager (GOCI) satellite time series were analyzed with dynamic factor analysis (DFA) to provide complementary dynamical context. Applied to spring observations in the Korean marginal seas, GLMM‐fingerprint clustering identified four clusters and increased redundancy analysis explanatory power relative to both the pooled data set (adjusted R 2 = 0.221) and a composition‐based clustering baseline. Phytoplankton community composition was most closely related to stratification in the Yellow Sea, mesoscale eddy/upwelling forcing in the East Sea, and contrasting warm‐current versus freshwater influences in the South Sea. The Yellow Sea cluster showed strong coherence with stratification‐related controls (adjusted R 2 = 0.847). Explanatory power remained lower in the East Sea cluster (adjusted R 2 = 0.272), consistent with mesoscale forcing that is difficult to capture using field covariates alone, whereas DFA‐based satellite diagnostics supported eddy/upwelling‐related variability. The South Sea separated into two clusters (adjusted R 2 = 0.492 and 0.424), reflecting contrasting warm‐current versus freshwater influences. This framework offers an interpretable pathway for mechanism‐oriented regionalization in dynamically complex coastal seas.