Shoot growth and crown development: effect of crown position in three-dimensional simulations
Bibliographic record
Abstract
Trees have been increasingly considered as modular organisms, with individual shoots forming autonomous units that respond semi-independently to their surrounding environment. However, there is evidence for fairly strict hormonal control of tree crown development. Studies on the hydraulic architecture of trees suggest a closer functional connection between shoots and crown development than is postulated by the theory of branch autonomy. We studied how shoot growth pattern influences growth and crown architecture in young Scots pine trees simulated by the LIGNUM model assuming that (a) the growth of a shoot mainly depends on its light climate and (b) the growth of a shoot is influenced by its position within the crown. We determined shoot position within the crown based on a recently developed vigor index. The vigor index compares the relative axis cross-sectional area from the base of the tree to each shoot and gives a value of 1 to the pathway of the greatest cross-sectional area. All other shoots attain values between 0 and 1 depending on their cross-sectional areas and the cross-sectional areas of the branches leading there from the main axis. The shoot light climate is characterized by annually intercepted photosynthetically active radiation. We compared the results from simulations (a) and (b) against an independent data set. The addition of a within-shoot position index (the vigor index) to our simulation (simulation b) resulted in a more realistic tree form than that obtained with simulation (a) alone. We discuss the functional significance of the results as well as the possibilities of using an index of shoot position in simulations of crown architecture.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".