Boreal forest provenance tests used to predict optimal growth and response to climate change: 2. Black spruce
Bibliographic record
Abstract
Height, diameter, and survival data were obtained from 20 range-wide black spruce ( Picea mariana (Mill.) BSP) provenance trials established from 1973 to 1977. Population response functions based on February minimum temperatures were developed for 23 Ontario and Great Lakes states provenances to predict climate values maximizing height growth for individual seed sources. Site transfer functions based on February maximum temperatures and May maximum temperatures were developed for five test sites to predict climate values maximizing height growth for test locations. Contour lines representing optimal performance were fitted to current (1961–1990) and future (2041–2070) climate grids. For black spruce seed sources from the east of Lake Superior and Lake Huron, optimal height growth was achieved between 45° and 47°N; for the western sources optimal performance moved north between 46° and 48°N. In eastern Ontario, height growth of northern sources may increase with transfer to warmer environments and with future temperature increases. Central sources are currently growing at or close to optimum and will be negatively affected by increased future temperatures. Southern sources may currently benefit from transfer to cooler environments, and the effects of global warming may cause significant height growth loss and the potential extirpation of local populations.
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) | 0.001 | 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 | 0.000 | 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".