Reproductive limitation mediates the response of white spruce (<i>Picea glauca</i>) to climate warming across the forest–tundra ecotone
Bibliographic record
Abstract
Shifts in the extent of the boreal forest during past warm intervals and correlations between climate and the position of the forest–tundra ecotone suggest that recent temperature increases will facilitate forest expansion into tundra ecosystems. In this study, we used a unique set of high-resolution repeat photographs to characterize white spruce (Picea glauca (Moench) Voss) populations in 1980 and 2015 at 52 sites across the forest–tundra transition in the Northwest Territories, Canada. We also conducted field inventories at eight sites to examine mapping accuracy, construct age distributions, and assess cone production and seed viability. Our analysis shows that stand density in the forest–tundra has increased significantly since 1980 but that the density of spruce at sites in the tundra has not changed. Age distributions constructed from field sampling also indicate that recent recruitment has occurred in the forest–tundra but not at tundra sites. The nonlinear relationship between summer temperature and seed viability suggests that recent warming has facilitated recruitment in the northern Subarctic but that cold temperatures still limit recruitment at higher latitude tundra sites. Additional research to determine the extent of changes in forest density across the northern Subarctic should be conducted to determine if similar changes are occurring across this ecotone.
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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 | 0.001 |
| 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 | 0.000 | 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".