Disturbance regimes of hemlock-dominated old-growth forests in northern New York, U.S.A.
Bibliographic record
Abstract
Old-growth forests often have complex, uneven age structures reflecting both the long time elapsed since a major disturbance and the periodic formation of small canopy gaps. I established 12 plots of 0.1 ha in four areas of old growth to describe the stand-scale disturbance regime of forests dominated by eastern hemlock (Tsuga canadensis (L.) Carrière) in northern Adirondack Park, N.Y., U.S.A. I analyzed radial-increment patterns of cores from all canopy trees (398 trees in total) on each plot to determine the date of accession to canopy for each tree. Major growth releases indicated disturbance events that resulted in either gap origin (16% of events) or release from suppression (82% of events). The average decadal rate of disturbance for all plots and decades of the 130-year period from 1850 to 1979 is 4.85.4% of current exposed crown area. The average canopy-tree residence time is 184211 years. The stand-scale disturbance regimes in these Adirondack forests are similar to those of hemlockhardwood forests in Wisconsin, Michigan, Pennsylvania, and New York. These hemlock-dominated old-growth stands appear to be in quasi-equilibrium when viewed together over 13 decades.
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 | 0.000 | 0.001 |
| 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".