Photosynthesis and light-use efficiency by plants in a Canadian boreal forest ecosystem
Bibliographic record
Abstract
Measurements of the photosynthetic response to midsummer irradiance were made for 11 species representing the dominant trees, understory shrubs, herbaceous plants and moss species in an old black spruce (Picea mariana (Mill.) B.S.P.) boreal forest ecosystem. Maximum rates of photosynthesis per unit foliage area at saturating irradiance, A(max), were highest for aspen (Populus tremuloides Michx.), reaching 16 micromol m(-2) s(-1). For tamarack (Larix laricina (Du Roi) K. Kock) and P. mariana, Amax was only 2.6 and 1.8 micromol m(-2) s(-1), respectively. Values of A(max) for understory shrubs and herbaceous plants were clustered between 9 and 11 micromol m(-2) s(-1), whereas A(max) of feather moss (Pleurozium schreberi (Brid.) Mitt.) reached only 1.9 micromol m(-2) s(-1). No corrections were made for differences in shoot structure, but values of photosynthetic light-use efficiency were similar for most species (70-80 mmol CO2 mol(-1)); however, they were much lower for L. laricina and P. mariana (15 mmol CO2 mol(-1)) and much higher for P. schreberi (102 m;mol CO2 mol(-1)). There was a linear relationship between Amax and foliage nitrogen concentration on an area basis for the broad-leaved species in the canopy and understory, but the data for P. mariana, L. laricina and P. schreberi fell well below this line. We conclude that it is not possible to scale photosynthesis from leaves to the canopy in this ecosystem based on a single relationship between photosynthetic rate and foliage nitrogen concentration.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".