Bridging the biomass data gap: A literature-based Length-Weight Relationship framework for estimating representative dry weights of freshwater invertebrates in Korean rivers

J Jaehoon Yeom M Minji Kim S Sang Don Kim

Abstract

Representative species weight is a critical ecological index for modeling, vulnerability assessment, and toxicity prediction, yet scientifically validated data for aquatic invertebrates remain limited. To address this gap, we present the first literature-based strategy to estimate and validate representative dry weights of freshwater invertebrate species in Korean rivers using Length-Weight Relationships (LWRs). Species length and dry weight records were compiled from domestic field guides, while dry weight records were compiled from both domestic and global literature. LWR coefficients (a and b) were then calculated at genus, family, and order levels and preprocessed under control conditions. Among the taxonomic levels tested, averaging genus-level coefficients yielded the highest concordance with field-measured dry weights (R 2  = 0.6633, n = 240), outperforming broader taxonomic levels. Furthermore, a logarithmic correlation analysis confirmed that greater numbers of LWR sources improve predictive accuracy, particularly at the genus level. Based on this optimal strategy, representative dry weights were estimated for 563 taxa. This methodology fills a critical data gap by leveraging existing literature to generate reliable species-specific weight indices without additional field measurements. Our approach provides a quantitative foundation for biomass estimation in data-limited freshwater ecosystems and supports improved ecological modeling, conservation planning, and machine learning-based impact prediction.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 21, Issue 6
Published June 23, 2026
Pages e0352157
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (3)

J

Jaehoon Yeom

M

Minji Kim

S

Sang Don Kim