Environmental-mediated relationships between tree growth of black spruce and abundance of spruce budworm along a latitudinal transect in Quebec, Canada
Bibliographic record
Abstract
Changes in tree growth and insect distribution are projected due to climate warming. The expected effectsof climate change on forest disturbance (e.g., insect outbreak) regime call for a better insight into thegrowth responses of trees to varying environmental conditions over geographical regions in eastern NorthAmerica. In this study, the effects of a latitudinal thermal gradient and spruce budworm (SBW) outbreakson the tree growth of black spruce (Picea mariana Mill.) were investigated along a 400 km transect from48◦N to 51◦N across the continuous boreal forest in Quebec, Canada. Time series data were analyzed tosynchronize climatic factors (temperature and precipitation trends), insect dynamics (SBW populationfrequency) and tree growth (ring-width chronology). Radial growth resulted as being synchronized withclimate patterns, highlighting a positive effect of maximum temperatures on tree growth, especially in thenorthernmost site. Increasing temperatures and precipitation had a more positive effect on tree growthduring epidemic periods, whereas the detrimental effects of SBW outbreaks on tree growth were observedwith climate patterns characterized by lowered temperature. The lag between time series, synchronyand/or frequency of synchrony between tree growth and SBW outbreak were considered in order tolink the growth of host trees and the dynamics of insect populations. The proposed analytical approachdefined damage severity on tree growth in relation to population dynamics and climate fluctuations atthe northern distribution limit of the insect. Overall, a decline in tree growth was observed in these borealforests, due to SBW outbreaks acting in combination with other stress factors.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".