Effect of ecosystem warming on boreal black spruce bud burst and shoot growth
Bibliographic record
Abstract
Abstract The boreal forest is predicted to experience the greatest warming of any forest biome during the next 50–100 years, but the effects of warming on vegetation phenology are not well known. The objectives of this study were to (1) examine the effects of whole ecosystem warming on bud burst and annual shoot growth of black spruce trees in northern Manitoba, Canada and (2) correlate bud burst to cumulative degree‐days (CDD). The experimental design was a complete randomized block design that consisted of four replicated blocks. Each replicate block contained four treatments: soil warming only (heated outside, HO), soil and air warming (heated inside, HI), control outside (no chamber, no heating, CO), and inside a chamber maintained at ambient conditions (no soil or air warming, control inside, CI). Bud burst was measured during the first and second years of the experiment, starting in 2004, and annual shoot growth was measured for the first 3 years (2004–2006) of the study. On average, shoot bud burst occurred 11 and 9 days earlier in 2004 and 2005, respectively, for HI than for other treatments. However, mean CDD required for bud burst for HI was within the standard deviation of CO for both years. In year 1 of the treatments, shoot bud burst occurred earlier for HI than other treatments (CI, CO, HO), but final shoot length of HI trees was less than in CO trees. In the second year of warming, final shoot length was not different for HI than CO. By the third year of warming final shoot length was significantly greater for HI than all other treatments. Empirical results from this study suggest that soil and air warming causes an earlier bud burst for all years of observation and greater shoot lengths by the third season of warming. A longer growing season and greater annual shoot growth should increase carbon uptake by boreal black spruce trees in a warmer climate.
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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 | 0.000 |
| 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 | 0.000 | 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".