Modeling the effects of fire and climate change on carbon and nitrogen storage in lodgepole pine (<i>Pinus contorta</i>) stands
Bibliographic record
Abstract
Abstract The interaction between disturbance and climate change and resultant effects on ecosystem carbon (C) and nitrogen (N) fluxes are poorly understood. Here, we model (using CENTURY version 4.5) how climate change may affect C and N fluxes among mature and regenerating lodgepole pine (Pinus contortavar.latifoliaEngelm. ex S. Wats.) stands that vary in postfire tree density following stand‐replacing fire. Both young (postfire) and mature stands had elevated forest production and net N mineralization under future climate scenarios relative to current climate. Forest production increased 25% [Hadley (HAD)] to 36% [Canadian Climate Center (CCC)], compared with 2% under current climate, among stands that varied in stand age and postfire density. Net N mineralization increased under both climate scenarios, e.g., +19% to 37% (HAD) and +11% to 23% (CCC), with greatest increases for young stands with sparse tree regeneration. By 2100, total ecosystem carbon (live+dead+soils) in mature stands was higher than prefire levels, e.g., +16% to 19% (HAD) and +24% to 28% (CCC). For stands regenerating following fire in 1988, total C storage was 0–9% higher under the CCC climate model, but 5–6% lower under the HAD model and 20–37% lower under the Control. These patterns, which reflect variation in stand age, postfire tree density, and climate model, suggest that although there were strong positive responses of lodgepole pine productivity to future changes in climate, C flux over the next century will reflect complex relationships between climate, age structure, and disturbance‐recovery patterns of the landscape.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".