Potential changes in carbon dynamics due to climate change measured in the past two decades
Bibliographic record
Abstract
Evidence suggests that climate change dynamics have been occurring in the northern latitudes for the past two and a half decades. The CENTURY ecosystem model was used for a set of simulations related to the carbon dynamics of interior Alaska taiga forest types. The functional dynamics of three age-classes (young, middle, and mature) of three ecosystem types (white spruce (Picea glauca (Moench) Voss), black spruce (Picea mariana (Mill.) BSP), and hardwoods) were compared using an average climate that was present prior to 1980 and the climate record from 1980 to 2000. Estimates for total ecosystem production indicate a decrease in tree carbon capture for hardwood stands for all three age-classes summed across a 20-year climate change period. White spruce displayed increases in carbon capture for the three age-classes. Young and mid-aged black spruce stands showed a decrease in ecosystem productivity. The old-growth black spruce stand showed a small increase in carbon capture. Dynamics displayed for the entire ecosystem (soil organic matter, tree dynamics, dead wood, and forest litter) followed the same trends as vegetation productivity. For the same 20-year climate period and across all three age-classes, carbon capture decreased for hardwood ecosystems and increased for white spruce ecosystems. The young black spruce system showed a change from a positive carbon balance to a negative carbon balance. Based on the landscape area covered by each vegetation type, we suggest that the net effect of climate warming over the past 20 years has been a substantial decrease in carbon capture in the forests of interior Alaska.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".