Abstract: Accurate estimation of vegetation biomass is a critical component for estimating terrestrial ecosystem carbon stocks. However, research on biomass estimation for herbaceous marshes remains limited. In this study, we collected 270 paired above-ground biomass (AGB) and trait data from reed marshes in Northeast China to estimate AGB, and 70 paired AGB and below-ground biomass (BGB) data from global literature to estimate BGB. The results showed that classifying reed marshes into saltwater and freshwater marshes greatly improved the model fit (R2 values of classified vs. overall models: >0.50 vs. >0.31 for AGB estimation and >0.50 vs. >0.10 for BGB estimation, respectively). A power-law allometric model using plant height as the sole predictor was optimal for AGB estimation, and the inclusion of plant density did not markedly enhance prediction accuracy. The power function also effectively described the relationship between AGB and BGB, with scaling exponents of 1.13 and 0.60 for saltwater and freshwater marshes, respectively. Our results indicate that saltwater and freshwater marsh classification is necessary for accurate wetland vegetation carbon estimation. These findings provide valuable insights into the prediction of carbon dynamics in wetland ecosystem and supports a better understanding of wetland carbon sequestration.

Key words: allometric equations, model evaluation, plant height, plant density, herbaceous marshes, vegetation carbon