Holocene reconstruction of the spruce budworm outbreak-fire interaction in the mixed boreal forest reveals a peculiar oscillation
Bibliographic record
Abstract
Characterizing millennial and multi-millennial variability in disturbance regimes will be crucial in improving knowledge within the context of a changing climate and the development of sustainable forest management practices in the eastern Canadian mixed boreal forest. The major biotic and abiotic disturbances in the mixed boreal forest are the spruce budworm, and fire, respectively. The ability to reconstruct the variability of these disturbance agents under different climate conditions over long time periods will help elucidate the interaction between the agents and their dynamics in the mixed boreal forest. The objective of this observational study was to reconstruct the frequency of large spruce budworm population (LSBP) and fire disturbance events, and describe their interaction in the mixed boreal forest over the course of the Holocene within the context of changing vegetation and climatic conditions. Lepidopteran scales and sedimentary charcoal were used to reconstruct the local/extra-local disturbance history from lake sediment along with pollen to reconstruct changes in tree species composition. Spruce budworm and fire disturbance events were determined using the CharAnalysis software. Regime shifts in disturbance event frequencies along with changes in tree composition were detected using Sequential T-test Analysis of Regime Shifts. Spearman’s correlation was used to determine the relationship between spruce budworm and fire event frequencies. Over the course of the Holocene, 57 LSBP events and 76 fire events were detected with event frequencies ranging between 0.75-6.30 events*kyr-1 and 1.71-10.5 events*kyr-1 respectively. Nine and 7 regime shifts in LSBP and fire event frequencies were detected respectively, along with 2 shifts in vegetation. A significant negative correlation was observed between LSBP and fire event frequencies from 6000-1000 BP suggestive of a linked disturbance interaction. The first local lake sediment multi-millennial disturbance regime reconstruction comprising both spruce budworm and fire in the mixed forest revealed a very peculiar oscillation in disturbance event frequencies. Each disturbance seemingly establishes a positive disturbance-vegetation feedback that favors itself and inhibits the occurrence of the other. Further, rapid climate change events may act as a key trigger in establishing the respective feedback loops resulting in the observed disturbance event frequency oscillation.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".