A trait-informed framework for assessing diatom indicator readiness in Korean monsoonal rivers
Abstract
Diatom indicators are widely used in river bioassessment; however, their operational value can be obscured when stress-gradient response, rainfall response, and external transferability are treated as equivalent properties. We evaluated recalculated benthic diatom indicators in Korean monsoonal rivers using a fixed raw or near-raw analytical core comprising a long-term community-environment dataset (3576 samples, 587 taxa), Geum 2015 calibration data (119 sites), independent Geum 2023 validation data (80 sites), paired pre–post rainfall records (1788 comparisons), and taxonomic/trait references. Circular reuse was avoided by excluding precomputed score sheets and review-based summaries. Hellinger ordination showed that assemblage structure was primarily associated with gradients of phosphorus enrichment, conductivity, organic pollution, turbidity, and substrate/burial. The recalculated trophic diatom index (TDI)-type metric (rTDI) and motile, saprophilous, and saproxenous taxa were more environmentally reliable than richness or Shannon diversity. Reverified rainfall analyses showed that source-record TDI decreased after rainfall, whereas recalculated rTDI increased; trait/guild pre–post effects were generally minor. External validation indicated that reliability and transferability were distinct properties. Motile taxa retained the strongest cross-dataset consistency and predictive contribution, whereas rTDI and organic-pollution affinity/sensitivity metrics remained conditionally transferable. This framework distinguishes among chronic gradient response, rainfall-associated biofilm reorganization, and validation-informed indicator use, thereby supporting more cautious interpretation of diatom metrics in monsoonal river biomonitoring.
Fields of Study & Subjects
Diatoms and Algae Research
Marine and coastal ecosystems
Aquatic Ecosystems and Phytoplankton Dynamics
Publication details
- Journal / source
- Ecological Indicators
- Publisher
- Elsevier BV
- Volume
- 189
- Pages
- 115157–115157
- Publication date
- 7 July 2026
- Language
- EN