A three decade assessment of climate‐associated changes in forest composition across the north‐eastern <scp>USA</scp>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Summary Climate‐associated changes in forest composition have been widely reported, particularly where changes in abiotic conditions have resulted in high mortality of sensitive species and have disproportionately favoured certain species better adapted to these newer conditions. In the north‐eastern USA and south‐eastern Canada, few studies have examined climate‐related influences associated with forest composition, and none have considered broad‐scale changes over a long temporal (>25 years) period. We used US Forest Service Forest Inventory and Analysis data from 1983 to 2014 across four north‐eastern states (Maine, New Hampshire, New York and Vermont) to assess temporal and spatial changes in the occurrence and abundance of American beech Fagus grandifolia Ehrh, sugar maple Acer saccharum L., red maple Acer rubrum L. and birch Betula spp. saplings. We also tested the effects of biotic and abiotic factors on the distribution of the four studied deciduous species over the entire period examined. Occurrence and abundance of American beech have increased substantially over the past three decades, whereas the occurrence and abundance of three other deciduous species have decreased in all ecological provinces of the north‐eastern USA, except the Midwest Broadleaf ecological province. Consequently, a clear shift in species composition is currently underway in the beech‐maple‐birch (BMB) forests of the north‐eastern USA, with uncertain consequences for future ecosystem structure and function. In the studied region and over the entire period examined, the distribution of increased occurrence and abundance of beech relative to the three other deciduous species were associated with higher temperature and precipitation as well as higher conspecific basal area and dead tree basal area. Synthesis and applications . The change from beech‐maple‐birch forests to more beech‐dominated forests with beech encroachment to new forest areas across the north‐eastern USA may continue if higher intensity harvesting and disturbances (i.e. large‐scale canopy openings) do not occur. This would be a significant management concern as beech is associated with a widespread bark disease, is commercially less desirable, and can limit natural regeneration from other species. Our results emphasize the need for management strategies such as higher intensity harvesting methods, vegetation control and limiting browsing pressure to reduce beech dominance.
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.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it