Branch Growth and Crown Dynamics in Northern Hardwood Forests
Bibliographic record
Abstract
The canopy is one of the last frontiers of forest research, due to the difficulty of gaining direct access to tree crowns, and the difficulty of identifying and measuring individual tree crowns from a distance. These challenges have limited our understanding of both tree growth and stand dynamics. This thesis examines ontogenetic trends in the diameter growth of tree trunks and radial growth of tree crowns, using a combination of ground-based inventory data and in-situ measurements taken from a mobile canopy lift. The main goal was to determine whether and why growth declines once trees reach the canopy. The inventory data revealed that both diameter and crown growth rates follow a hump-shaped trend, and that the crown area of many large trees shrank over time, suggesting that the decline in expansion rates is the net effect of declining growth and increasing dieback. The in-situ measurements confirmed that dieback increases with tree size, suggesting that tree sway increases as trees grow larger, resulting in more frequent collisions between neighboring crowns. Indeed, dieback was higher in tree crowns located within 3 m of another crown, confirming that dieback is in part the result of inter-crown collisions. In-situ measurements of lateral branch growth were also taken before and after gap formation to examine species- and size-specific responses to canopy disturbance. Yellow birch did not respond significantly to gap formation, but sugar maple and beech did. On the other hand, small trees responded more to gap formation than large trees. Following release, small trees grew faster than large trees, but lateral growth did not vary with branch length or tree height, suggesting that growth declines due to increased reproduction, rather than increased support costs or hydraulic limitation. Indeed, in-situ measurements confirmed that large trees that produced a lot of seeds grew less than small trees that produced few seeds. Overall, this research indicates that disturbance acts in concert with declining growth and increased dieback to offset the size-asymmetry of light competition, favoring small trees that can grow laterally to exploit light in canopy gaps, as well as web of narrow spaces between crowns of canopy trees.
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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) | 0.001 | 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".