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Record W4220936512 · doi:10.5194/egusphere-egu22-6529

IMPLEMENTING A TERRESTRIAL NITROGEN AND PHOSPHORUS CYCLE IN THE UVIC ESCM: Validation and first results 

2022· preprint· en· W4220936512 on OpenAlexaff
Makcim De Sisto, Andrew H. MacDougall

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsSt. Francis Xavier UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsNitrogenPhosphorusChemistry

Abstract

fetched live from OpenAlex

Nitrogen and phosphorus biogeochemical dynamics are crucial for the regulation of the terrestrial carbon cycle. In ESMs and EMICS the implementation of nutrient limitation has shown to improve the carbon feedbacks representation and hence, the response of land to atmospheric CO2 rising in simulation scenarios. We aimed to implement a nitrogen and phosphorus cycle in the UVic ESCM to improve projections of the future CO2 fertilization feedbacks. The nitrogen cycle is a modified version of the original N model developed in 2012, the basic structure was left in place with the most prominent changes being the enforcement of N mass conservation and the merger with a deep land-surface and wetland module that allowed the estimation of N2O and NO fluxes. The N cycle estimates fluxes from three organic (litter, soil organic matter and vegetation) and 2 inorganic (NH4+and NO3-) pools, it accounts inputs from biological nitrogen fixation and N deposition. The P cycle contains the same organic pools with one inorganic P pool, it estimates influx of P from rock weathering and losses from leaching and occlusion. Two historical simulations were carried for the different nutrient limitation setups of the model: CN and CNP, with a control run that consisted in an only C cycle simulation. The N cycle now conserves mass, the original and added fluxes (NO and N2O), along with the N and P pools are within the range of other studies and literature. The implementation of nutrient limitation resulted in a reduction of GPP from the CN (125 Pg yr-1) and CNP (111 Pg yr-1) simulations compared the C only control (148 Pg yr-1) by the year 2020; which implies that the model efficiently represents a nutrient limitation over the CO2fertilization effect. Furthermore, the tropical latitudes in the CNP simulation resulted in a reduction of 33% of the mean GPP and 41% of the vegetation biomass compared to the C only run; these results are in better agreement with observations and with the notion that P limitation have been shown to limit vegetation specially in tropical regions. In summary, the implementation of the nitrogen and phosphorus cycle have successfully enforced a nutrient limitation in the terrestrial system, which now have reduced the primary productivity and the capacity of land to uptake atmospheric carbon.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.015
GPT teacher head0.241
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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