Eastern white pine and eastern hemlock growth: possible tradeoffs in response of canopy trees to climate
Bibliographic record
Abstract
A warming climate and extended growing season may confer competitive advantages to temperate conifers that can photosynthesize across seasons. Whether this potential translates into increased growth is unclear, as is whether pollution could constrain growth. We examined two temperate conifers — eastern white pine (Pinus strobus L.) and eastern hemlock (Tsuga canadensis (L.) Carrière) — and analyzed associations between growth (476 trees in 23 plots) and numerous factors, including climate and pollutant deposition variables. Both species exhibited increasing growth over time and eastern white pine showed greater maximum growth. Higher spring temperatures were associated with greater growth for both species, as were higher autumnal temperatures for eastern hemlock. Negative correlations were observed with previous year (eastern hemlock) and current year (eastern white pine) summer temperatures. Spring and summer moisture availability were positively correlated with growth for eastern white pine throughout its chronology, whereas for hemlock, correlations with moisture shifted from being significant with current year’s growth to previous year’s growth over time. The growth of these temperate conifers might benefit from higher spring (both species) and fall (eastern hemlock) temperatures, though this could be offset by reductions in growth associated with hotter, drier summers.
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 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 | 0.003 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".