Development of a New TRIPLEX-Insect Model for Simulating the Effect of Spruce Budworm on Forest Carbon Dynamics
Bibliographic record
Abstract
The spruce budworm (SBW) defoliates and kills conifer trees, consequently affecting carbon (C) exchanges between the land and atmosphere. Here, we developed a new TRIPLEX-Insect sub-model to quantify the impacts of insect outbreaks on forest C fluxes. We modeled annual defoliation (AD), cumulative defoliation (CD), and tree mortality. The model was validated against observed and published data at the stand level in the North Shore region of Québec and Cape Breton Island in Nova Scotia, Canada. The results suggest that TRIPLEX-Insect performs very well in capturing tree mortality following SBW outbreaks and slightly underestimates current annual volume increment (CAI). In both mature and immature forests, the simulation model suggests a larger reduction in gross primary productivity (GPP) than in autotrophic respiration (Ra) at the same defoliation level when tree mortality was low. After an SBW outbreak, the growth release of surviving trees contributes to the recovery of annual net ecosystem productivity (NEP) based on forest age if mortality is not excessive. Overall, the TRIPLEX-Insect model is capable of simulating C dynamics of balsam fir following SBW disturbances and can be used as an efficient tool in forest insect management.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".