Height development of Scots pine on peatlands: describing change in site productivity with a site index model
Bibliographic record
Abstract
The effect of site properties and forest drainage on the dominant height development of Scots pine (Pinus sylvestris L.) stands in peatland sites was studied using data from permanent sample plots located in natural and drained sites in northern Finland. The Korf model was used to describe the height development of dominant trees in natural sites. The effect of drainage on height development was accounted for by a term giving a nonlinear height increase for drained sites as a function of the time elapsed since drainage. The variance component model was applied to account for the hierarchical data structure. Natural height development after 30 years of age at DBH was significantly slower in PF sites (sparsely forested pine fens) than in PS sites (genuine forested pine swamps). Within PF sites, there were further differences in relation to nutrient availability. Temperature sum explained the variation in the intercept. In PS sites, drainage resulted in a moderate increase in the maximum attainable height, while in PF sites, drainage improved site productivity by 80%85% in terms of the attainable height. The asymptote for drained stands was dependent on stand age at the time of drainage. Differences between the two major groups were assumed to be due to initial differences in site water regime.
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".