Are biotic disturbance agents challenging basic tenets of growth and yield and sustainable forest management?
Bibliographic record
Abstract
We examined the performance of older even-aged plantations to check the validity of three of the most fundamental tenets of forest site productivity: the height–age site index, Eichhorn's rule and the thinning response hypothesis. We assessed the condition of >14 000 trees in 60 randomly selected plantations to determine whether the stands were following site productivity expectations and growth and yield projections. We evaluated the health status of all the trees by height class (<2, 2–4 and >4 m tall). We found strong evidence that older, managed plantations are subject to damage agents that are targeting dominant trees. We found natural ingress was not filling voids created by loss of planted trees. Our findings were clearly in conflict with the assumptions of low and stable levels of loss of dominant trees in aging plantations. The tendency of forest growth models to emphasize stability and predictability needs to be reconsidered. The assumptions driving the traditional forest growth models were developed largely in the absence of biotic and abiotic damage agents and certainly prior to the knowledge of climate change. The combined influence of these two drivers must be better accounted for in growth models through more intensive stand and forest level monitoring.
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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".