Functional Redundancy and Structural Flexibility as Contrasting Plankton Strategies Under Macrotidal Pulses

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Authors: Quedyane Silva da Cruz
Cited by: 0

Abstract

Macrotidal estuaries function as high-energy pulse systems, where hydrodynamic forces continuously reconfigure the environment. While seasonal dynamics are well documented, the short-term mechanisms that allow plankton to persist in these hyperdynamic environments are still poorly understood. In this study, we investigated how the structure and functional characteristics of planktonic communities from a tropical Ramsar site on the Amazonian coast respond to tidal oscillations on a short timescale. Integrating high-frequency sampling with feature-based machine learning, we observed the effects of tidal energy and lunar phases. We demonstrated that phytoplankton and zooplankton employ divergent adaptive strategies to cope with physical stress. Phytoplankton exhibited functional redundancy, maintaining a stable functional structure despite the high rate of taxonomic turnover driven by tidal oscillations. On the other hand, zooplankton exhibited high structural flexibility, characterized by a strong coupling between taxonomic composition and functional characteristics, leading to synchronous reorganization of the entire community. Random Forest Models identified bottom-up effects as governing community dynamics, where hydrodynamic forcing modulates upward controls, specifically nitrogen availability for phytoplankton and resource quality for zooplankton. Our analyses led us to infer contrasting adaptive strategies of estuarine persistence, in which redundancy in producers and flexibility in consumers allow coexistence under extreme physical conditions. These findings establish that capturing the high-frequency pulse of macrotidal systems is essential for mechanistic ecological understanding and effective biodiversity monitoring.

Fields of Study & Subjects

Marine and coastal ecosystems Marine Biology and Ecology Research Aquatic Ecosystems and Phytoplankton Dynamics

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
17 February 2026
Language
EN
Document type
Dataset