Long‐term dynamics in a planted conifer forest with spontaneous ingrowth of broad‐leaved trees
Bibliographic record
Abstract
Abstract Question: What are the age structure and growth trends in a 160‐year old not‐managed Pinus sylvestris plantation with spontaneous development of Quercus robur and can recruitment of Q. robur be related to the radial growth pattern of the P. sylvestris overstorey? Location: Mattemburgh forest reserve, The Netherlands. Methods: Throughout the forest, we sampled 103 oaks and 102 pines with an increment corer. Tree ring widths were measured and cross‐dated to produce mean ring width series. With these data we determined tree ages, investigated growth trends and identified growth releases and suppressions. Results: Q. robur is uneven‐aged: some individuals recruited around 1925, but most reached coring height in the 1940s. The latter recruitment period related to a transition from stressed to released growth of the overstorey pines, growth releases of the oldest Q. robur and occurrence of P. sylvestris regeneration. No further recruitment has taken place since 1950. Conclusions: This study demonstrates that an old pine plantation can develop spontaneously into well‐structured pine forest with an understorey of oak and pine. However, understorey recruitment in these forest types is not a continuous process and in this case a single allogenic canopy disturbance triggered its establishment.
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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".