Smallman (2026) The contemporary global terrestrial carbon cycle - a systemic model-data fusion analysis

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Open MIND
• Year: 2026
• Date: 2026-01-01
• Authors: T. Luke Smallman
• DOI: 10.7488/ds/8094

Research Groups

[Information not provided in the paper text.]

Short Summary

This study presents a rigorous, global, multi-decadal, data-informed analysis of the terrestrial carbon cycle using a Bayesian model-data fusion framework to calibrate an ecosystem model. It reveals that current global multi-decadal datasets are largely insufficient to confidently determine the sign of net carbon exchange across most of the vegetated land surface.

Objective

• To provide a rigorous, uncertainty-bounded, and systemic analysis of terrestrial carbon dynamics and their underpinning ecological processes using a state-of-the-art model-data fusion framework.
• To enhance accessibility of the resulting open-access dataset through a thorough description of its key features, calibration and evaluation metrics, photosynthate allocation fractions, tissue residence times, and their uncertainties.

Study Configuration

• Spatial Scale: Global, with a resolution of 0.5 degrees by 0.5 degrees (approximately 55 kilometers by 55 kilometers at the equator).
• Temporal Scale: Multi-decadal (2003-2024), with a monthly time step.

Methodology and Data

• Models used: CARDAMOM (Carbon Data Model fusiOn and valiDatiOn Metamodel) Bayesian model-data fusion framework, calibrating DALEC (Data Assimilation Linked Ecosystem Carbon) intermediate complexity terrestrial ecosystem model.
• Data sources: Ecologically relevant spatio-temporal observations (leaf area index, absorbed photosynthetically active radiation, gross primary production, woody biomass, soil carbon), and forcing data (meteorology, atmospheric carbon dioxide concentration, burned area, and forest loss).

Main Results

• Current global multi-decadal datasets are inadequate to provide greater than 95% confidence on the sign of net carbon exchange across 91% of the vegetated land surface.
• For the portion of the vegetated land surface where confidence exceeds 95% (approximately 9% of the total), it was determined that 0.23% of the total vegetated land surface acts as a net carbon source, 0.75% as a net carbon sink, and 7.3% as neutral.
• The CARDAMOM framework uniquely propagates observational uncertainties through to the retrieved DALEC parameters (ecosystem properties) and simulates carbon pools and fluxes for each of 55,246 pixels.

Contributions

• Provides a rigorous, global, multi-decadal, and systemic analysis of the terrestrial carbon cycle with explicit uncertainty propagation, which is a significant advancement over existing incomplete or inconsistent state and flux products.
• Offers an open-access dataset with detailed descriptions of calibration, evaluation metrics, allocation fractions, and residence times, along with their uncertainties.
• The dataset can inform the evaluation of computationally expensive land surface models that cannot be directly constrained with model-data fusion approaches.
• Identifies key uncertainties in carbon cycle understanding, serving as a first step for targeted research and mitigation strategies.

Funding

[Information not provided in the paper text.]

Citation

@article{Smallman2026contemporary,
  author = {Smallman, T. Luke},
  title = {The contemporary global terrestrial carbon cycle - a systemic model-data fusion analysis},
  journal = {Open MIND},
  year = {2026},
  doi = {10.7488/ds/8094},
  url = {https://doi.org/10.7488/ds/8094}
}