Analysis of nitrogen controls on carbon and water exchanges in a conifer forest using CLASS-CTEMᴺ⁺ model
Bibliographic record
Abstract
Nitrogen (N) controls on carbon and water exchanges were analyzed in a 70-year old eastern temperate conifer forest in Ontario, Canada from 2003 to 2007 using a newly developed nitrogen (N) cycle coupled model -- CLASS-CTEMᴺ⁺. This process-based model incorporates sunlit and shaded big-leaves for C3 and C4 photosynthesis and semi-mechanistic canopy conductance formulation for dynamic plant-functional-types. Recently, key soil and plant N cycling algorithms have also been included (e.g., biological fixation, atmospheric N deposition, fertilization, mineralization, nitrification, denitrification, leaching, soil nitrous dioxide (N₂0) emissions, root N uptake, plant N allocation and N controls on plant photosynthesis capacity). The simulated values of soil-plant N contents and processes rates including N₂0 fluxes were generally in agreement with observations. Comparison of default non-N and C&N-coupled model simulations clearly revealed N controls on photosynthetic uptake and water loss. Predictions of daily gross ecosystem productivity (GEP), ecosystem respiration (Re), net ecosystem productivity (NEP) and evapotranspiration (ET) showed better agreement with eddy covariance (EC) flux measurements when using the N-coupled model (RMSE of 1.97, 0.73, 1.44, 0.92; and MAE of 1.48, 0.55, 1.01, 0.60 for GEP, Re, NEP, and ET, respectively; n=1825) as compared to the non-N model simulations (RMSE of2.95, 1.35, 1.93, 1.03; MAE of2.38, 1.15, 1.55,0.71 for GEP, Re, NEP, and ET, respectively; n=1825) over 5 years (2003-2007). Annual values of N-coupled model simulated NEP were 134, 195, 183, 225 and 255 g C m⁻² yr⁻¹ for 2003-2007, as compared to non-N model simulated annual NEP values, which were 535, 562, 507, 540, and 535 g C m⁻² yr⁻¹ for respective years. These values were compared to measured NEP values of 220±67, 126±67, 33±67, 142±67 and 102±67 g C m⁻² yr⁻¹ for the years 2003-2007, respectively. The difference between N-coupled model simulated and EC measured annual variations of carbon exchanges was largely due to specific extreme weather events (e.g. drought, spring warming) during certain years. Overall, the impacts of N limitations on carbon fluxes were more pronounced during early spring, late autumn and winter seasons. This newly developed model will help to evaluate the response of terrestrial vegetation ecosystems to N variations under different scenarios for future climate change.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".