Divergent temporal trends of net biomass change in western Canadian boreal forests
Bibliographic record
Abstract
Abstract Forests play a strong role in the global carbon cycle by absorbing atmospheric carbon dioxide through increasing forest biomass. Understanding temporal trends of forest net above‐ground biomass change (Δ AGB ) can help infer how forest carbon sequestration responds to ongoing climate changes. Despite wide spatial variation in the long‐term average of climate moisture availability ( CMI average ) across forest ecosystems, temporal trends of Δ AGB associated with CMI average remain unclear. We tested the hypothesis that the negative impacts of climate change on Δ AGB would decrease with CMI average using the data from permanent sample plots, monitored from 1958 to 2011, with stand ages varying from 17 to 210 years, in western boreal forests of Canada. We found that Δ AGB on average increased with CMI average . Temporally, Δ AGB declined sharply between 1958 and 2011 in plots with low CMI average owing to increased biomass loss from mortality accompanied by little growth gain, whereas Δ AGB changed little in plots with high CMI average . The temporal decrease of Δ AGB in drier areas was attributable to its negative responses to warming‐induced temporal decreases in climate moisture availability. Synthesis . Our results indicate that large‐scale changes in forest carbon functioning associated with climate change depend on the long‐term average of climate moisture availability. Our finding suggests a possible retreat of boreal biome at the drier distribution limits with predicted declines in water availability in the 21st century.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".