Climate and nutrient influences on the growth of white spruce trees in the boreal forests of the Yukon
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The boreal forests of North America are undergoing major changes because of the direct effects of global warming and increased CO 2 levels. Plant production in the boreal forest is nutrient limited, and we examined how long-term fertilization affected growth of white spruce Picea glauca in the face of these major changes. We conducted a large-scale experiment by fertilizing two 1 km 2 stands of white spruce in the southwestern Yukon with commercial NPK fertilizer from 1987 to 1994. Tree growth was measured by the width of annual increments in 60 trees from each of 2 control and of 2 matched fertilized 1 km 2 sites for the period from 1977 to 1997 in a before, during, and after experimental design. Ring widths increased in both control and fertilized trees over this period as summer temperatures increased. Ring widths in fertilized trees increased from 9 to 48% over control trees during the years in which fertilizer was added, but immediately fell back to control levels from 1995 to 1997 at 1 site as soon as fertilization was stopped. In the long term, nitrogen in these forests may become tied up in shrubs, grasses, herbs, and fungi and not be available to the trees. There are 2 other possible explanations for this lack of sustained tree growth: first, the conversion of nitrogen into a form not readily available to spruce and, second, a spruce bark beetle outbreak that hit the southwestern Yukon during and after 1994 and affected 1 study site much more than the other.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it