Effect of terrestrial nutrient limitation on the estimation of the remaining carbon budget
Bibliographic record
Abstract
Abstract. The carbon cycle plays a foundational role in the estimation of the remaining carbon budget. It is intrinsic for the determination of the transient climate response to cumulative CO2 emissions and the zero-emissions commitment. For the terrestrial carbon cycle, nutrient limitation is a core regulation on the amount of carbon fixed by terrestrial vegetation. Hence, the addition of nutrients such as nitrogen and phosphorus in land model structures in Earth system models is essential for an accurate representation of the carbon cycle feedback in future climate projections. Therefore, the estimation of the remaining carbon budget is impacted by the representation of nutrient limitation in modelled terrestrial ecosystems; however, it is rarely accounted for. Here, we estimate the carbon budget and remaining carbon budget of a nutrient-limited Earth system model, using nitrogen and phosphorus cycles to limit vegetation productivity and biomass. We use eight Shared Socioeconomic Pathways (hereafter SSP) scenarios and idealized experiments with three distinct model structures: (1) carbon cycle without nutrient limitation, (2) carbon cycle with terrestrial nitrogen limitation, and (3) carbon cycle with terrestrial nitrogen and phosphorus limitation. To capture the uncertainty in the remaining carbon budget, three different climate sensitives were tuned for each model version. Our results show that, overall, nutrient limitation reduced the remaining carbon budget for all simulations in comparison with the carbon cycle without nutrient limitation. Between nitrogen and nitrogen–phosphorus limitation, the latter had the lowest remaining carbon budget. The mean remaining carbon budgets obtained from the SSP scenario simulations for the 1.5 °C target in the non-nutrient-limited, nitrogen-limited, and nitrogen–phosphorus-limited models were 228, 185, and 175 Pg C, respectively, relative to the year 2020. For the 2 °C target, the mean remaining carbon budget values were 471, 373, and 351 Pg C for the non-nutrient-limited, nitrogen-limited, and nitrogen–phosphorus-limited models, respectively, relative to the year 2020. This represents a reduction of 19 % and 24 % for the 1.5 °C target and 21 % and 26 % for the 2 °C target for the respective nitrogen- and nitrogen–phosphorus-limited simulations compared with the non-nutrient-limited model. These results show that terrestrial nutrient limitation constitutes an important factor to be considered when estimating or interpreting remaining carbon budgets and that it is an essential uncertainty in the remaining carbon budgets from Earth system model simulations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".