Adverse climatic periods precede and amplify defoliator‐induced tree mortality in eastern boreal North America
Bibliographic record
Abstract
Abstract As major alterations are occurring in climate and pest ranges, it is imperative to evaluate their combined contribution to tree mortality in order to propose mitigation measures and limit losses in forest productivity. The objective of this study was to explore the association between declines in tree growth resulting from climatic and biotic (spruce budworm) disturbances, and their interactions on tree mortality of two dominant tree species, Abies balsamea and Picea mariana, of the eastern North‐American boreal forest. We disentangle the influences of abiotic and biotic components on growth through a combination of model‐data comparison techniques. First, we characterized the variability in tree growth and mortality in the study area using a network of tree‐ring width measurements collected from living and dead trees. Subsequently, a bioclimatic simulation model was used to estimate the past annual, nonlinear, responses of stand‐level net primary production ( NPP ) to climate variability (period 1902–2012). From these two data sources, we defined the biotic stress events as the variance in the tree‐ring data unexplained by the bioclimatic forest growth simulation. Throughout the 20th century, two periods of adverse climatic conditions preceded spruce budworm outbreaks episodes and induced tree mortality. Climatic stress events were associated with cold springs, warmer than average summers. We found that past stress history in interaction with tree characteristics and species predisposed trees to mortality. In addition, co‐occurring events (climatic and biotic) increased the severity of mortality episodes. Synthesis . Our study challenges the belief that spruce budworm outbreak is the primary driver of broad‐scale tree mortality in eastern boreal forest. Rather, tree mortality is the result of cumulative events that combine unfavourable conditions for growth, resulting in loss of tree vigour and subsequently, mortality. Co‐occurrence of stresses in the future may lead to more severe episodes of mortality, as extreme climatic events become more frequent.
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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".