Exploring Carbon Cycling in Aquatic Ecosystems Using Novel Analytical and Data-Driven Approaches
Submission deadline: Tuesday, 1 December 2026
Available journals: Earth's Future, Geophysical Research Letters, Global Biogeochemical Cycles, JGR: Biogeosciences, JGR: Oceans or JGR: Machine Learning and Computation
Background:
Aquatic ecosystems play a fundamental role in the global carbon cycle, with both organic carbon (OC) and inorganic carbon (IC) pools contributing to essential biogeochemical processes that influence ecosystem health, biodiversity, and climate regulation. Organic carbon, which encompasses the carbon stored in living organisms and organic matter, is crucial for microbial food webs, nutrient cycling, and the production of greenhouse gases, while inorganic carbon, primarily as dissolved carbonates, significantly impacts water chemistry, pH stability, and carbon sequestration. Together, these forms of carbon underpin the biological and chemical stability of aquatic environments. Despite the importance of OC and IC in aquatic systems, many aspects of their sources, sinks, transformations, and interactions remain poorly understood, particularly under the pressures of anthropogenic and global environmental changes. Traditional research methods have provided valuable insights, yet they often struggle to capture the complexity and variability of carbon processes in real-time and across different scales. The limited understanding of carbon cycling dynamics in aquatic ecosystems highlights a critical gap, making it challenging to predict ecosystem responses to climate change and develop sustainable management strategies. Recent technological advances allow for deeper, real-time monitoring of carbon cycling in aquatic ecosystems. However, the large size, high dimensionality, and inherent uncertainty of the data generated present challenges. To address these, advanced data analysis methods, including machine learning, big data synthesis, and predictive modeling, are essential for uncovering hidden patterns, extracting meaningful insights, enhancing predictive capabilities, and managing uncertainty. This Special Collection seeks submissions that leverage new technologies and data-driven approaches to advance our understanding of carbon cycling in aquatic ecosystems.
Topics for this call for papers include but are not restricted to:
·Technological advancements and novel methodologies for real-time in situ monitoring of carbon dynamics in aquatic ecosystems
·Data-driven models and big data approaches to understand and predict carbon cycling
·Interactions between organic and inorganic carbon pools and their implications for aquatic ecosystems
·New insights into the sources, transport, and transformation of organic and inorganic carbon in diverse aquatic ecosystems
