Leaf and canopy conductance in aspen and aspen-birch forests under free-air enrichment of carbon dioxide and ozone
Bibliographic record
Abstract
Increasing concentrations of atmospheric carbon dioxide (CO2) and tropospheric ozone (O3) have the potential to affect tree physiology and structure, and hence forest feedbacks on climate. Here, we investigated how elevated concentrations of CO2 (+45%) and O3 (+35%), alone and in combination, affected conductance for mass transfer at the leaf and canopy levels in pure aspen (Populus tremuloides Michx.) and in mixed aspen and birch (Betula papyrifera Marsh.) forests in the free-air CO2-O3 enrichment experiment near Rhinelander, Wisconsin (Aspen FACE). The study was conducted during two growing seasons, when steady-state leaf area index (L) had been reached after > 6 years of exposure to CO2- and O3-enrichment treatments. Canopy conductance (g(c)) was estimated from stand sap flux, while leaf-level conductance of sun leaves in the upper canopy was derived by three different and independent methods: sap flux and L in combination with vertical canopy modelling, leaf 13C discrimination methodology in combination with photosynthesis modelling and leaf-level gas exchange. Regardless of the method used, the mean values of leaf-level conductance were higher in trees growing under elevated CO2 and/or O3 than in trees growing in control plots, causing a CO2 x O3 interaction that was statistically significant (P < or = 0.10) for sap flux- and (for birch) 13C-derived leaf conductance. Canopy conductance was significantly increased by elevated CO2 but not significantly affected by elevated O3. Investigation of a short-term gap in CO2 enrichment demonstrated a +10% effect of transient exposure of elevated CO2-grown trees to ambient CO2 on g(c). All treatment effects were similar in pure aspen and mixed aspen-birch communities. These results demonstrate that short-term primary stomatal closure responses to elevated CO2 and O3 were completely offset by long-term cumulative effects of these trace gases on tree and stand structure in determining canopy- and leaf-level conductance in pure aspen and mixed aspen-birch forests. Our results, together with the findings from other long-term FACE experiments with trees, suggest that model assumptions of large reductions in stomatal conductance under rising atmospheric CO2 are very uncertain for forests.
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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 | 0.000 | 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".