Long-term stability of northern hardwoods across a topographic gradient and variations in harvest methods
Bibliographic record
Abstract
Increased emphasis on forest complexity, resilience, and biodiversity has renewed interest in northern hardwood forests. In parallel, there is concern of impacts of traditional, timber-oriented regeneration methods on successional trajectories and tree communities. To ensure compatibility of emerging goals with site biological capacity, assessment of common silvicultural methods across forest conditions is imperative. This work utilizes a long-term dataset of 407 sampling plots from the Bartlett Experimental Forest in New Hampshire, USA, over 70 years. Topographic and meteorological variables were utilized to test the effects of site conditions and silviculture on tree species diversity and composition. Results show a decline in diversity over time that reflects a shift toward dominance of late successional species, which vary with site-specific conditions. The effect of silviculture was not detectable, and differences in tree communities were attributed to pre-existing conditions of site variables prior to installation of experimental treatments. Tree diversity and composition for both 1932 and 2003 measurements were correlated with solar insolation, local wind speed, and hydrological catchment area. The collective findings highlight the long-term stability of species under past silvicultural regimes, that some areas are more facilitative/limiting to goals of enhancing tree biodiversity and emerging technologies can capture species–site interactions in northern hardwoods.
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 | 0.001 | 0.001 |
| 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".