MODELLING THE TERRESTRIAL NITROGEN AND PHOSPHORUS CYCLE IN THE UVic ESCM 
Bibliographic record
Abstract
The role of nitrogen and phosphorus in terrestrial ecosystems has been shown to be critical in the regulation of the terrestrial carbon cycle. Therefore, the implementation of nutrient limitation in Earth System Models should be considered in order to have a more accurate representation of carbon fluxes, vegetation distribution and the response of the biosphere to climate change. Previous attempts to introduce the terrestrial nitrogen cycle and nutrient limitation in the UVic ESCM resulted in an incomplete project that was not added to the regular structure of the model. Here, we intend to improve the current state of the terrestrial nitrogen cycle and to develop a new terrestrial phosphorus cycle that will be coupled to the carbon cycle. The most prominent changes in the N cycle are the enforcement of N mass conservation and the merge with a deep land surface and a new wetland model. The N and P cycles estimates the fluxes between three organic pools: litter, soil and vegetation compartments (leaf, root and wood), two N pools (NH4+, NO3-) and one inorganic P pool. The basic structure of the N cycle was left in place, it estimates the inputs via biological nitrogen fixation and outputs via leaching, furthermore, with the merger with the new wetland model denitrification was added to the N loss of the system. The P cycle accounts the inputs from estimations of rock weathering and losses from occlusion and leaching. Both cycles regulate the vegetation system in 2 ways: (1) by controlling vegetation biomass if nutrient is limiting, reducing the amount of carbon in the plant compartments until the C:N or C:P ratio is met and (2) directly regulating the primary productivity by taking into account the relationship between leaf N and P and the maximum carboxylation rate (Vcmax). We aim to improve projections of the future CO2 fertilization feedback, and thus carbon budgets and ZEC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".