Effects of soil temperature on parameters of a coupled photosynthesis-stomatal conductance model
Bibliographic record
Abstract
To examine the effects of soil temperature on a coupled photosynthesis-stomatal conductance model, seedlings of trembling aspen (Populus tremuloides Michx.), jack pine (Pinus banksiana Lamb.), black spruce (Picea Mariana (Mill.) B.S.P.) and white spruce (Picea glauca (Moench) Voss) were exposed to soil temperatures ranging from 5 to 35 degrees C for 4 months. Light and CO(2) response curves of foliar gas exchange were measured for model parameterization. The effects of soil temperature on four key model parameters, V(cmax) (maximum rate of carboxylation), J(max) (maximum rate of electron transport), alpha (energy conversion efficiency or quantum efficiency of electron transport) and R(d) (daytime dark respiration), were modeled using two third-order polynomial equations and a modified Arrhenius equation. In all species, V(cmax) and J(max) increased with soil temperature up to an optimum, and then decreased with further increases in soil temperature. In the conifers, alpha showed a similar response to soil temperature as V(cmax) and J(max), but soil temperature had no significant effect on alpha in aspen. Soil temperature had no significant effect on R(d) in any species. The three equations described the relationships between soil temperature and the model parameters reasonably well, but performed best for V(cmax) and worst for alpha. No significant relationships were identified between soil temperature and the parameters of the stomatal conductance model.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".