Heterogeneity in ponderosa pine/Douglas-fir forests: age and size structure in unlogged and logged landscapes of central Colorado
Bibliographic record
Abstract
Tree age and size structures were compared within and among topographic categories in portions of a 35-km2unlogged landscape and a comparable adjacent logged landscape. Tree density was generally higher in the logged landscape. One fifth of plots in the unlogged landscape had trees older than 400 years, but no trees older than 400 years remained in the logged landscape plots. Ten recruitment pulses were identified for the unlogged study area, accounting for 49% of all trees measured during 26% of the 421-year survival record. Recruitment pulses in the logged area accounted for fewer trees during a larger amount of time. Most recruitment periods in the unlogged landscape coincided with known past major fires. The mixed-severity historical fire regime created openings that persisted for as long as 148 years. The following components exist in the unlogged landscape: (i) forest patches having a distinct age cap reflecting regeneration following an earlier stand-replacing fire, (ii) uneven-aged forest patches having no evidence of an age cap, (ii) openings created by fire, and (iv) riparian areas. Results suggest that the logged landscape is poised to regain an old-growth age distribution, and tree removal in the logged landscape could restore the size distribution found in the unlogged landscape. However, the unlogged landscape has openings not found in the logged landscape that should be considered in restoration efforts at a landscape scale.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".