Journal Article
Modeling Growth, Mortality, and Detachment of Sessile Marine Organisms: An Integrated DEB-Statistical Approach
Teng Tu; Jinxin Zhou; Daisuke Kitazawa; Akane Takahashi; Yoshinobu Yoneyama; Masanobu Hasebe
Journal of Marine Science and Engineering · Vol. 13, Issue 10 · pp. 1858 · 2025
Abstract
Sessile marine organisms form the foundation of many coastal ecosystems, playing crucial roles in functions like water filtration and habitat provision. Understanding their population dynamics—particularly the interplay of growth, reproduction, and detachment under environmental stress—is essential for both ecological research and effective coastal management. This work presents a comprehensive numerical model for simulating the growth, reproduction, mortality and detachment of sessile organisms using a hybrid dynamic energy budget (DEB)–statistical approach. Our model incorporates bioenergetic processes, environmental stress responses, space competition, and layering dynamics. The simulation framework considers the effects of temperature, salinity, dissolved oxygen, and food availability on organism physiology while tracking growth, reproduction, and mortality and detachment. Model validation was performed using field data collected from sessile invertebrate populations around a floating platform in the estuary of the Sumida River in Tokyo, Japan, from September 2002 to September 2003. Our approach successfully reproduced observed patterns with high accuracy. The model revealed that temperature stress and salinity fluctuations interact synergistically, amplifying mortality and detachment rates beyond what would be predicted by each factor independently. Comparative analyses with reduced models lacking either mortality or detachment components demonstrated the importance of including both processes for the accurate prediction of population dynamics. Our case study provides a robust framework for predicting sessile organism responses to environmental variability and highlights key areas for future research in benthic ecosystem modeling.