Disentangling the effect of drought on stand mortality and productivity in northern temperate and boreal forests
Bibliographic record
Abstract
Abstract It has recently been reported that changing precipitation patterns increase tree mortality and reduce biomass accumulation in northern temperate and boreal forests. Functional diversity can mitigate the impacts of climate extremes in different types of ecosystems, but few studies have focused on tree functional diversity in forest ecosystems. It is critical to identify functional traits that could help anticipate the impact of drought on tree mortality, and how these affect above‐ground tree biomass productivity at the ecosystem level. We tested how three functional traits (ratio of dry leaf mass per unit area [ LMA ], xylem pressure at which 50% of stem xylem conductivity is lost through cavitation [Ψ 50 ] and leaf area to sapwood ratio) influence severe drought impacts on stand mortality and productivity. We used structural equation modelling to compare the effect of a latent variable composed of these three traits between plots that had suffered drought and plots that had not, on the mortality and productivity of northern temperate and boreal forests of Québec, Canada. A latent variable composed of LMA and Ψ 50 significantly explained drought‐induced tree mortality, but did not explain stand productivity response to severe drought. Therefore, even if these traits relate to the ability of species to survive drought (drought tolerance) at the tree level, they did not affect the maintenance of plant productivity during drought events (drought resistance) at the stand scale. We hypothesize that the effect of tree mortality on productivity was likely compensated by the formation of canopy openings that stimulate the growth of surviving trees. Synthesis and applications . Our results show that mitigation of water loss and xylem resistance to cavitation contribute similarly to severe drought tolerance in trees within northern temperate and boreal forests. Therefore, including drought‐resistant trees in fine‐scale mixtures might mitigate the impacts of drought on forest productivity due to the survivors’ response to released resources.
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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 | 0.001 | 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".