Light extinction coefficients specific to the understory vegetation of the southern boreal forest, Quebec
Bibliographic record
Abstract
This study was conducted in six different forest types in Abitibi, Que., (i) to identify the factors that most influence understory light transmission in the southern boreal forest and (ii) to develop light extinction coefficients (k), which could be used to simulate light transmission in the understory. Light availability and understory vegetation (cover, composition, vertical distribution, and leaf area index) were characterized within three strata (0.05-5 m) in a total of 180 quadrats. Calculated k values were based on measured light availability and leaf area index. These values varied among forest types, strata, understory vegetation types, and cover in the upper stratum. The highest k values were generally associated with a dense stratum of Acer spicatum Lam. We developed five sets of k values based on the factors that most affected light transmission. Measured transmission (T m ) was compared with transmission predicted (T p ) from each set of k values. Light transmission predicted using a single k value (mean k = 0.54) underestimated T m . More accurate predictions were obtained when we used the other four sets of k values. Our results indicate that, in the southern boreal forest, the understory vegetation can be quite heterogeneous and patterns of light transmission cannot be accurately simulated using a unique k value. However, the various sets of k values developed in this study could be used in prediction models of forest dynamics to obtain relatively good predictions of understory light extinction in forest types similar to the ones studied here.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 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) | 0.001 | 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 teacher head, 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".