Trait-based mechanisms underpin regional hotspot of diatom-driven carbon export in an oligotrophic gyre

Abstract. The oligotrophic subtropical gyres, vast yet nutrient-poor, pose challenges to our understanding of efficient carbon sequestration. Here, we integrate taxonomic, sediment trap, and metagenomic analyses to investigate the mechanisms underlying regionally heterogeneous and efficient diatom-mediated carbon export in the western North Pacific Subtropical Gyre. We discovered that within a vertically stratified nutrient regime, diatom communities displayed clear niche partitioning: Navicula and Rhizosolenia were enriched in the nutrient-depleted surface mixed layer, while Nitzschia, Chaetoceros, and Thalassiosira tended to dominate the deep chlorophyll maximum – reflecting hydrographic control over community assembly. This trait-based community structuring directly influenced the composition and magnitude of diatom carbon export, with fluxes ranging from 10³ to 10⁵ cells m⁻² d⁻¹ and an estimated 0.13–194.85 μg C m⁻² d⁻¹. Total carbon export and export efficiency (carbon exported relative to production) was markedly enhanced at station affected by the Kuroshio (K2b), which was mainly driven by the large, carbon-rich Rhizosolenia, delineating a distinct regional hotspot. Critically, metagenomic analysis revealed a limited presence of bacteria genes encoding key carbohydrate-active enzymes capable of degrading diatom-derived fucose-containing sulfated polysaccharides (FCSP), indicating a key biochemical mechanism that may reduce organic matter remineralization and enhance flux preservation. Our findings establish a multi-process framework wherein hydrodynamic regimes select for export-prone diatom communities with specific functional traits (e.g., size, carbon content), and the biochemical resistance of their organic byproducts may synergistically promote efficient carbon export. This study deciphers the interacting controls on carbon sequestration heterogeneity in the oligotrophic ocean, with crucial implications for predicting the biological pump's response to global change.