Modelling environmental controls on ecosystem photosynthesis and the carbon isotope composition of ecosystem‐respired CO<sub>2</sub> in a coastal Douglas‐fir forest
Bibliographic record
Abstract
We developed and applied an ecosystem-scale model that calculated leaf CO2 assimilation, stomatal conductance, chloroplast CO2 concentration and the carbon isotope composition of carbohydrate formed during photosynthesis separately for sunlit and shaded leaves within multiple canopy layers. The ecosystem photosynthesis model was validated by comparison to leaf-level gas exchange measurements and estimates of ecosystem-scale photosynthesis from eddy covariance measurements made in a coastal Douglas-fir forest on Vancouver Island. A good agreement was also observed between modelled and measured delta13C values of ecosystem-respired CO2 (deltaR). The modelled deltaR values showed strong responses to variation in photosynthetic photon flux density (PPFD), air temperature, vapour pressure deficit (VPD) and available soil moisture in a manner consistent with leaf-level studies of photosynthetic 13C discrimination. Sensitivity tests were conducted to evaluate the effect of (1) changes in the lag between the time of CO2 fixation and the conversion of organic matter back to CO2; (2) shifts in the proportion of autotrophic and heterotrophic respiration; (3) isotope fractionation during respiration; and (4) environmentally induced changes in mesophyll conductance, on modelled delta(R) values. Our results indicated that deltaR is a good proxy for canopy-level C(c)/C(a) and 13C discrimination during photosynthetic gas exchange, and therefore has several applications in ecosystem physiology.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".